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Location: Dublin, Ireland Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? As a Mid-Market Account Executive, you will be a key member of the team leading the growth of our new business. We’re building a world-class sales organization, and the road ahead is going to be very exciting. At Fin, we are striving to do sales differently. We are asking our customers to put Fin at the core of their businesses, and we can only do this by putting them at the core of ours. We strongly believe in the overall growth and continued development of each new hire. In joining the Account Executive team at Fin, you join a community that believes in development and promotion from within. As a rapidly expanding business, there is a high degree of opportunity for progression, creativity, and ownership. What will I be doing? Evangelize our product by spearheading the growth and adoption of Fin across our Mid-Market segment Manage the full sales cycle for Fin's Mid Market customers, from prospecting to close, through a consultative sales approach Provide timely and accurate forecasts and clear visibility on revenue performance Maintain up-to-date knowledge of our evolving products and processes Create your own demonstrations, tailored to client needs Engage in team development and mentoring Represent the voice of the customer to cross-functional partners, including Marketing and Product Contribute to the overall growth of the global Enterprise business, pioneering new best practices and driving projects to up level the team What skills do I need? 5+ years experience as an Account Executive 3+ years of SaaS experience selling similar products Strong sales instincts and track record hitting and exceeding quota Exceptional written and verbal communication Fluent German (Business Level) Comfortable and energized operating and problem-solving in a fast-moving organization, working inbound and outbound opportunities across a range of industries and company sizes Ability to close net new business in a competitive landscape Exhibits a growth mindset, intellectual curiosity, and ambition Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Location: Poland; Ukraine; Georgia Workplace: Remote Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. What you will do - Deliver end-to-end data science projects using classical machine learning (e.g., regression, classification, time series forecasting) and deep learning approaches — from data exploration and modeling to deployment and performance tracking. - Collaborate closely with business stakeholders to identify opportunities and translate them into measurable data-driven solutions. - Present complex analytical findings in a clear, actionable way to both technical and non-technical audiences. - Contribute to analytical planning and ensure alignment with overall business objectives. - Support presales activities by preparing data/ML solution concepts, participating in client meetings, and estimating project scope and potential value. - Help shape the Data Science practice by contributing to its strategic development and supporting recruitment initiatives. What you bring - Proven experience as a Data Scientist delivering end-to-end projects — from exploratory data analysis to model deployment, performance evaluation, and experimentation (e.g., A/B testing). - Strong expertise in working with tabular and time-series data, including EDA, feature engineering, predictive modeling, and model evaluation. - Proficiency in Python and common data-science libraries (e.g., pandas, scikit-learn, TensorFlow/PyTorch). - Experience leading or mentoring analytics teams and coordinating with business stakeholders. - Excellent communication skills, able to translate between technical and business perspectives effectively. - Solid understanding of business processes and data structures. - Confidence in client-facing settings: gathering requirements, shaping analytical roadmaps, and delivering measurable business value. - Fluency in English for meetings with international clients. Nice to have - Hands-on experience with deep learning, computer vision, or generative AI projects. - Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps tools. - Experience with data visualization or BI tools for communicating insights. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Location: New York; San Francisco; Toronto; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: Our team is a fast-growing group of committed researchers and engineers. The mission of the team is to build reliable machine learning systems and optimize audio inference serving efficiency using innovative techniques. As an engineer on this team, you will work on advancing core audio model serving metrics, including latency, throughput, and quality by diving deep into our systems, identifying bottlenecks, and delivering creative solutions for audio processing and streaming workloads. You’ll collaborate closely with both the training and serving infrastructure teams to ensure seamless integration between model development and deployment, with a special focus on real-time and streaming audio inference. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. Qualifications: - Significant experience developing high-performance audio or machine learning inference systems. - Proficiency with programming languages such as C++ and Python. - Hands-on experience with deep learning models for audio, speech, or language applications. - A bias for action and a strong results-oriented mindset. It is a big plus if you also have considerable experience with: - GPU programming, low-level system optimization, model parallelization techniques over multiple GPUs - Have experience with duplex real-time streaming architectures. - Internals of machine learning frameworks for audio (such as PyTorch, TensorFlow, or specialized audio libraries). - Have experience with inference framework like vLLM, SGLang, Tensort-LLM, or custom distributed inference systems - Sequence modeling (e.g., transformers for audio/speech) and end-to-end audio pipeline optimization Working location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: New York; San Francisco; Toronto; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: Our team is a fast-growing group of researchers and engineers focused on building reliable ML systems and pushing the boundaries of LLM inference efficiency. We develop techniques that improve how models execute in production, driving lower latency, higher throughput, and consistent quality across diverse workloads. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. Job Responsibilities: As an engineer on this team, you’ll work across the inference stack to improve core performance metrics by diving deep into model execution, identifying bottlenecks, and developing innovative optimizations. You’ll collaborate closely with modeling and systems teams to experiment, measure, and ship improvements that meaningfully accelerate inference. As the team evolves, you’ll have opportunities to build expertise in advanced performance techniques, including GPU/CUDA optimizations, kernel-level improvements, and model execution strategies for MoE and large-scale architectures. Qualifications: - 5+ years of experience writing high-performance, production-quality code - Strong programming skills in C++ or Python (Rust/Go also welcome) - Experience working with large language models and familiarity with the LLM inference ecosystem (e.g., vLLM, SGLang, etc.) - Ability to diagnose and resolve performance bottlenecks across the model execution stack - A strong bias for action — you ship fast, measure impact, and iterate It’s a big plus if you have experience with: - GPU programming, CUDA, or low-level systems optimization - Language modeling with transformers (MoE, speculative decoding, KV-cache optimizations) - Scaling performance-critical distributed systems (e.g., computation, search, storage) Working Location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. We’re looking for researchers and engineers to join our efforts. People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do "biology" or "neuroscience" of neural networks using “microscopes” we build, or as treating neural networks as binary computer programs we're trying to "reverse engineer". A few places to learn more about our work and team at a high level are this introduction to Interpretability from our research lead, Chris Olah ; a discussion of our work on the Hard Fork podcast produced by the New York Times, and this blog post (and accompanying video) sharing more about some of the engineering challenges we’d had to solve to get these results. Some of our team's notable publications include A Mathematical Framework for Transformer Circuits , In-context Learning and Induction Heads , Toy Models of Superposition , Scaling Monosemanticity , and our Circuits’ Methods and Biology papers. This work builds on ideas from members' work prior to Anthropic such as the original circuits thread , Multimodal Neurons , Activation Atlases , and Building Blocks . We aim to create a solid foundation for mechanistically understanding neural networks and making them safe (see our vision post ). In the short term, we have focused on resolving the issue of "superposition" (see Toy Models of Superposition , Superposition, Memorization, and Double Descent , and our May 2023 update ), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent work found millions of features in Sonnet, one of our production language models, represents progress in this direction. In our most recent work, we develop methods that allow us to build circuits using features and use this circuits to understand the mechanisms associated with a model's computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Haiku 3.5, one of our production models.” This is a stepping stone towards our overall goal of mechanistically understanding neural networks. We often collaborate with teams across Anthropic, such as Alignment Science and Societal Impacts to use our work to make Anthropic’s models safer. We also have an Interpretability Architectures project that involves collaborating with Pretraining. Responsibilities: Develop methods for understanding LLMs by reverse engineering algorithms learned in their weights Design and run robust experiments, both quickly in toy scenarios and at scale in large models Create and analyze new interpretability features and circuits to better understand how models work. Build infrastructure for running experiments and visualizing results Work with colleagues to communicate results internally and publicly You may be a good fit if you: Have a strong track record of scientific research (in any field), and have done some work on Interpretability Enjoy team science – working collaboratively to make big discoveries Are comfortable with messy experimental science. We're inventing the field as we work, and the first textbook is years away You view research and engineering as two sides of the same coin. Every team member writes code, designs and runs experiments, and interprets results You can clearly articulate and discuss the motivations behind your work, and teach us about what you've learned. You like writing up and communicating your results, even when they're null To learn more about the skills we look for and how to prepare for this role, see our blog post – So You Want to Work in Mechanistic Interpretability? Familiarity with Python is required for this role. Role Specific Location Policy: This role is based in San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Note: we don't have open Research Manager positions on the Interpretability team at this time. However, we're actively growing our team of Research Engineers and Research Scientists . If you're excited about interpretability research and open to an individual contributor role, we encourage you to apply. About the Interpretability team When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team’s mission is to reverse engineer how trained models work, and Interpretability research is one of Anthropic’s core research bets on AI safety. We believe that a mechanistic understanding is the most robust way to make advanced systems safe. People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do "biology" or "neuroscience" of neural networks, or as treating neural networks as binary computer programs we're trying to "reverse engineer". We aim to create a solid scientific foundation for mechanistically understanding neural networks and making them safe (see our vision post ). We have focused on resolving the issue of "superposition" (see Toy Models of Superposition , Superposition, Memorization, and Double Descent , and our May 2023 update ), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent work which found millions of features in Claude 3.0 Sonnet, one of our production language models, represents progress in this direction. In our most recent work , we developed methods that allow us to build circuits using features and use these circuits to understand the mechanisms associated with a model's computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Claude Haiku 3.5, one of our production models.” This is a stepping stone towards our overall goal of mechanistically understanding neural networks. A few places to learn more about our work and team are this introduction to Interpretability from our research lead, Chris Olah, Stanford CS25 lecture given by Josh Batson, and TWIML AI podcast with Emmanuel Ameisen. Some of our team's notable publications include and our Circuits’ Methods and Biology papers, Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet , Towards Monosemanticity: Decomposing Language Models With Dictionary Learning , A Mathematical Framework for Transformer Circuits , In-context Learning and Induction Heads , and Toy Models of Superposition . This work builds on ideas from members' work prior to Anthropic such as the original circuits thread , Multimodal Neurons , Activation Atlases , and Building Blocks . About the role As a manager on the Interpretability team, you'll support a team of expert researchers and engineers who are trying to understand at a deep, mechanistic level, how modern large language models work internally. Few things can accelerate this work more than great managers. Your work as manager will be critical in making sure that our fast-growing team is able to meet its ambitious safety research goals over the coming years. In this role, you will partner closely with an individual contributor research lead to drive the team's success, translating cutting-edge research ideas into tangible goals and overseeing their execution. You will manage team execution, careers and performance, facilitate relationships within and across teams, and drive the hiring pipeline. If you're more interested in making individual direct technical contributions to our research as the primary focus of your role, feel free to apply to our Research Scientist or Research Engineer roles instead. Key responsibilities Partner with a research lead on direction, project planning and execution, hiring, and people development Set and maintain a high bar for execution speed and quality, including identifying improvements to processes that help the team operate effectively Coach and support team members to have more impact and develop in their careers Drive the team's recruiting efforts, including hiring planning, process improvements, and sourcing and closing Help identify and support opportunities for collaboration with other teams across Anthropic Communicate team updates and results to other teams and leadership Maintain a deep understanding of the team's technical work and its implications for AI safety You may be a good fit if you Are an experienced manager (minimum 2-5 years) with a track record of effectively leading highly technical research and/or engineering teams Have a background in machine learning, AI, or a related technical field Actively enjoy people management and are experienced with coaching and mentorship, performance evaluation, career development, and hiring for technical roles Have strong project management skills, including prioritization and cross-functional coordination and collaboration Have managed technical teams through periods of ambiguity and change Are a quick learner, capable of understanding and contributing to discussions on complex technical topics and are motivated to learn about our research Are a strong communicator both in speaking and in writing Believe that advanced AI systems could have a transformative effect on the world, and are passionate about helping make sure that transformation goes well Strong candidates may also have Experience scaling engineering infrastructure Experience working on open-ended, exploratory research agendas aimed at foundational insights Some familiarity with our work and mechanistic interpretability Role-Specific Location Policy This role is expected to be in our SF office for 3 days a week. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000 — $500,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. Think of us as doing "neuroscience" of neural networks using "microscopes" we build - or reverse-engineering neural networks like binary programs. More resources to learn about our work: Our research blog - covering advances including Monosemantic Features and Circuits An Introduction to Interpretability from our research lead, Chris Olah The Urgency of Interpretability from CEO Dario Amodei Engineering Challenges Scaling Interpretability - directly relevant to this role 60 Minutes segment - Around 8:07, see a demo of tooling our team built New Yorker article - what it's like to work on one of AI's hardest open problems Even if you haven’t worked on interpretability before, the infrastructure expertise is similar to what's needed across the lifecycle of a production language model: Pretraining: Training dictionary learning models looks a lot like model pretraining - creating stable, performant training jobs for massively parameterized models across thousands of chips Inference: Interp runs a customized inference stack. Day-to-day analysis requires services that allow editing a model's internal activations mid-forward-pass - for example, adding a "steering vector" Performance: Like all LLM work, we push up against the limits of hardware and software. Rather than squeezing the last 0.1%, we are focused on finding bottlenecks, fixing them and moving ahead given rapidly evolving research and safety mission The science keeps scaling - and it's now applied directly in safety audits on frontier models, with real deadlines. As our research has matured, engineering and infrastructure have become a bottleneck. Your work will have a direct impact on one of the most important open problems in AI. Responsibilities: Build and maintain the specialized inference and training infrastructure that powers interpretability research - including instrumented forward/backward passes, activation extraction, and steering vector application Resolve scaling and efficiency bottlenecks through profiling, optimization, and close collaboration with peer infrastructure teams Design tools, abstractions, and platforms that enable researchers to rapidly experiment without hitting engineering barriers Help bring interpretability research into production safety audits - with real deadlines and high reliability expectations Work across the stack - from model internals and accelerator-level optimization to user-facing research tooling You may be a good fit if you: Have 5-10+ years of experience building software Are highly proficient in at least one programming language (e.g., Python, Rust, Go, Java) and productive with Python Are extremely curious about unfamiliar domains; can quickly learn and put that knowledge to work, e.g. diving into new layers of the stack to find bottlenecks Have a strong ability to prioritize the most impactful work and are comfortable operating with ambiguity and questioning assumptions Prefer fast-moving collaborative projects to extensive solo efforts Are curious about interpretability research and its role in AI safety (though no research experience is required!) Care about the societal impacts and ethics of your work Are comfortable working closely with researchers, translating research needs into engineering solutions. Strong candidates may also have experience with: Optimizing the performance of large-scale distributed systems Language modeling fundamentals with transformers High Performance LLM optimization: memory management, compute efficiency, parallelism strategies, inference throughput optimization Working hands-on in a mainstream ML stack - PyTorch/CUDA on GPUs or JAX/XLA on TPUs Collaborating closely with researchers and building tooling to support research teams; or directly performed research with complex engineering challenges Representative Projects: Building Garcon , a tool that allows researchers to easily instrument LLMs to extract internal activations Designing and optimizing a pipeline to efficiently collect petabytes of transformer activations and shuffle them Profiling and optimizing ML training jobs, including multi-GPU parallelism and memory optimization Building a steered inference system that applies targeted interventions to model internals at scale (conceptually similar to Golden Gate Claude but for safety research) Role Specific Location Policy: This role is based in the San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $315,000 — $560,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Chicago, Illinois Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? We’re building Fin's Scaled Customer Success team to reach more customers, provide consistent high-impact outcomes, and lean even harder into what makes us unique: our AI-powered products (especially Fin) and deep domain expertise. As a Scaled Customer Success Manager, you’ll be the customer’s trusted guide—helping them adopt and embed Fin's suite at scale, extracting real value, and scaling processes so more businesses succeed, more reliably. If you’re excited by working at the intersection of AI, product adoption, and operational excellence—and you want to help define how scaled CS works in practice—this is your role. What will I be doing? Drive broad product adoption, with special focus on Fin and AI-powered features: helping customers understand how Fin can automate support, enhance service, and deliver self-serve experiences, alongside human support. Design, implement, and iterate on engagement strategies and playbooks that can scale across customer segments—leveraging technology, automation, digital content, and smart touchpoints. Own implementation and onboarding conversations for your customers, ensuring they are being set up for success from Day 1. Monitor usage & health signals proactively—identifying risks, opportunities, and expansion paths; drive intervention where needed. Collaborate closely with Sales, Solution Engineering, Education, and Product to ensure a seamless customer journey from purchase through expansion. Act as the Voice of the Customer: feed insights from scaled engagements back into the product roadmap, feature improvements, messaging, and internal training. Help define what “Scaled CS” means here: you’ll be a builder—defining processes, tools, metrics, and models for what high volume, high value looks like. What skills do I need? 3-5 years of experience in a customer-facing role in SaaS / technology / product success or similar, with a track record of managing many customers or high-volume engagement. Strong interest in / experience with AI & automation support tools; ability to explain AI/Fin features and use cases to customers, and help them build workflows around them. Comfortable discussing technical topics such as APIs, integrations, and workflows—not an expert, but confident engaging with customers on technical questions and guiding them to resources. Excellent communication skills: can break down complex product and technical topics clearly for different audiences (executives, operations, support leaders). Data-driven mindset: able to monitor usage metrics, define success metrics, analyse what is / isn’t working, and adapt strategy based on results. Self-starter, entrepreneurial, comfortable in ambiguity; able to build processes from scratch and consistently improve them. Strong relationship builder: you can maintain trust even with many customers, manage expectations, and partner with internal stakeholders. Bonus skills & attributes Interest in consumption or usage-based SaaS models. Exposure to Generative AI, chatbots, virtual agents, or AI-assisted support tools. Experience in operations, scaling CS / onboarding / customer education / digital engagement programs. *Proof of eligibility to work in the United States is required. The OTE range for candidates within the Greater Chicago Area is $135,300 - $161,550. Actual base pay will depend on a variety of factors such as education, skills, experience, location, etc. The base pay range is subject to change and may be modified in the future. All regular employees may also be eligible for the corporate bonus program or a sales incentive (target included in OTE) as well as stock in the form of Restricted Stock Units (RSUs). Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Manager on the AI-Native GTM team at Anthropic, you'll lead a team of 5-10 Growth Account Executives responsible for driving expansion and retention across our fastest-growing AI-Native customers. You'll build and develop a high-performing team while establishing the frameworks, processes, and best practices that enable them to help customers harness the transformative potential of safe, frontier AI. In this role, you'll be responsible for growing team revenue, driving optimal commercial outcomes, and ensuring Anthropic is building long-term partnerships with the world’s fastest growing AI native startups. Responsibilities: Lead, coach, and develop a team of 5-10 Account Executives, providing regular feedback and guidance to drive both individual and team performance Own team revenue targets, developing strategies to accelerate growth Build scalable frameworks and processes for deal negotiations, account planning, quarterly business reviews, and customer health monitoring Partner with Product, Marketing, and other GTM teams to identify and execute on strategic growth opportunities across the startup portfolio Regularly review customer health metrics and collaborate with team members to develop action plans for at-risk accounts Mentor team members in developing consultative sales skills, negotiation best practices, and technical understanding of AI applications Drive operational excellence through pipeline management, forecasting accuracy, and team productivity metrics Participate in strategic customer conversations and support Growth AEs in complex negotiations You may be a good fit if you have: 10+ years of experience in enterprise software sales or account management, with 3+ years leading sales teams Proven track record of consistently exceeding team revenue targets and developing high-performing account executives Strong understanding of the startup ecosystem and experience working with high-growth technology companies Deep expertise in strategic account planning and scaling account management processes in a fast-paced environment Strong analytical and problem-solving skills with a data-driven approach to decision making Excellence in cross-functional collaboration and stakeholder management Background in technical product sales, particularly in areas like APIs, infrastructure, or ML/AI solutions Demonstrated ability to coach and develop talent while maintaining high performance standards The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $380,000 — $450,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Bucharest, Romania Workplace: hybrid WELCOME TO OLX   At OLX, we work together to build a more sustainable world through trade.   In Romania, we are 100+ people working for OLX, Storia.ro, and Autovit.ro—both from home and our cozy office in the center of Bucharest.   OLX is the leader of the classifieds market, helping millions of people make the smart choice every day – creating more space at home, repairing a broken pipe, or, just like you, finding the best job.   Autovit.ro is the market leader of the auto classifieds industry, connecting drivers to the cars that will take them where they need and want to be.   We are looking for a new colleague to join our team as a Business Development Manager for Strategic Partners, Motors (m/f) in our outstanding hub in Bucharest. A solid background in B2B sales in the Romanian Motors and/or Banking industry will be a big plus. What responsibilities will you get when working with us? Continuously focusing on growing and searching for new strategic clients (OEMs, Banks, Insurance Companies, and Government Authorities) and opportunities. Developing a database of qualified leads through referrals, telephone calls, canvassing, face-to-face interactions, and especially networking will be highly beneficial. Applying a consultative problem-solving approach to understand sophisticated client requirements and transform them into highly effective branding and revenue-generating solutions. Identifying decision-makers within targeted leads and initiating the sales process. Leading long-lasting relationships with clients by providing support, information, and innovative ways for them to reach results-oriented goals. Coordinating the implementation of the high-quality projects you will develop for the ongoing success and happiness of our clients (with the help of the OLX team). Preparing reports by collecting, analyzing, and summarizing information, and building on that to generate more business. Meeting sales and operational targets. What will you need to be successful in this role? Min. 3 years of confirmed experience as a sales consultant and a strong background in the Auto and/or banking industry. A permanent focus on spotting any potential impactful partnerships. Excellent communication, interpersonal, presentation delivery, and negotiation skills. An upbeat, mature, accountable, growth-minded, fast learner with strong analytical skills. Success in qualifying opportunities involving multiple key decision makers, including C-level individuals. Able to operate Microsoft Office; Online sales experience or auto industry experience is a plus. Proven experience in opportunity qualification, pre-call planning, call control, account development, and time management. High proficiency in both written and spoken English. University or college degree in Computer Science, Marketing would be preferred. What can you expect from us and what do we offer? Outstanding opportunity to become part of an international group, working for leading classifieds brands. The local company is based in an awesome-designed office in the centre of Bucharest. Continuous investment in your development, as well as the possibility to stay in contact with other professionals from all over the world. Complex compensation package (annual performance-based bonus, medical insurance, flexible benefits compensation). A dynamic and friendly environment where getting stuff done and enjoying the ride are far more important than rules and hierarchies. Being able to make your own smart choices. Diversity, Equity, and Inclusion at OLX   OLX values diversity and welcomes applicants of all races, ethnicities, disabilities, ages, genders, sexual orientations, religions, backgrounds, and experiences to apply. If this role excites you, we encourage you to apply, even if you don’t meet all the requirements - you may be just the right fit for this or other opportunities with us!   OLX will process your personal data to assess your fit for the applied position. You may optionally consent to store your data for up to 12 months after the application process for consideration in future OLX roles. For more details on how your application data will be processed, please check our Privacy Statement.

Location: viena, Austria Are you passionate about making a difference in mental health? Join Intellect as a Clinical Provider, where you’ll play a vital role in supporting clients on their journeys toward better mental health and personal growth through our cutting-edge telehealth platform. This freelance, remote role offers complete flexibility, allowing you to set your own business hours. It’s a perfect opportunity to complement your current job or private practice. While we prefer local candidates, we’re open to professionals from diverse locations who are aligned with our mission. Why Join Us? Become part of a collaborative network of Clinical Psychologists and Counsellors dedicated to expanding access to quality mental health care. At Intellect, you’ll find a supportive community focused on enhancing lives and helping clients overcome personal challenges. What You'll Do Provide 1-on-1 telehealth/or onsite mental health support for Intellect’s clients Address a range of clinical cases, including depression, anxiety, trauma, schizophrenia, eating disorders, addiction, and more Partner with our internal clinical team to improve the platform and client programs Requirements Requirements Qualifications: Master’s degree in Counseling or Clinical Psychology Expertise: Skilled in Cognitive Behavioral Therapy or other evidence-based approaches (e.g., Motivational Interviewing, DBT, SFBT) Experience: A minimum of 300 clinical hours post-master’s degree Languages: Proficiency in English and your local language Preferred Background: Prior experience with EAP, adult counseling, or coaching managerial roles Flexibility: Openness to occasional onsite work, if necessary, is a plus If you’re ready to make a meaningful impact and be part of a mission-driven team, we’d love to hear from you. Apply today and join us in transforming mental health care!

Location: Wollongong, Australia At Intellect, we’re a leading global mental health tech company in 100+ markets worldwide. We partner with employers, insurers, and governments to deliver coaching, counselling, and therapy services across Australia. We’re expanding our EAP provider network and hiring coaches, counsellors, and psychologists. Whether you’d like to supplement your private practice or take on a full-time career pathway, Intellect offers flexibility to fit your lifestyle. Why Join Us? Flexibility in employment models: freelance, contracted, part-time, or full-time — so you can maintain your own private caseload/clients while expanding with Intellect Competitive compensation & attractive perks Minimal admin burden — we handle scheduling, billing, client matching Regular supervision & CPD included Diverse client base — from local employees to regional/global Fortune 500 companies Additional opportunities: CISP (Critical Incident Stress Programme), webinars, in-person seminars, clinical leadership What You’ll Do Provide 1:1 telehealth and/or onsite coaching, counselling, or therapy-style consultations, offering general advice only (not treatment) Deliver CISP (Critical Incident Stress Programme) virtually or onsite as needed Facilitate webinars and in-person seminars (optional) Support employees with wellbeing, stress, and resilience Collaborate with Intellect’s internal clinical team to improve EAP programs Requirements Must Haves Counsellors & Clinical Psychologists Counsellors: Master’s in Counselling, Counselling Psychology, or Social Work Active membership/registration with one of: ACA (Australian Counselling Association) PACFA (Psychotherapy & Counselling Federation of Australia) AASW (Australian Association of Social Workers) 1–3 years of supervised counselling experience (internship counts if part of licensure pathway) Clinical Psychologists: Master’s in Clinical Psychology from an APAC-accredited program General registration with AHPRA (Psychology Board of Australia) Area of Practice Endorsement in Clinical Psychology preferred (or in progress via Registrar Program) 1–3 years of supervised clinical practice (internship counts if accredited/licensure pathway) Nice to Haves Experience working with First Nations / Aboriginal & Torres Strait Islander communities Background in managerial or leadership support (e.g., coaching managers, HR advisory) Prior EAP or workplace counselling experience Additional languages Flexibility for occasional onsite sessions Willingness for Police Check and/or Working With Children Check (not mandatory, only if requested by some clients) Eligibility/willingness to obtain a Medicare provider number (not mandatory, only if required by engagement type) Let’s Talk This is more than a job. It’s your chance to: Work with a global provider network Broaden your clientele base beyond local users Grow your career outside of sessions through research, content, and webinars Access supervision & CE most EAPs don’t provide If you’re ready to make a meaningful impact and expand your practice with flexibility, we’d love to hear from you.  Apply today and join Intellect in transforming workplace mental health across the country and beyond.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Staff level Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. Responsibilities Design and implement data processing infrastructure for large language model training (highly performant, reproducible, traceable) Develop and maintain core processing primitives (e.g., tokenization, deduplication, chunking) with a focus on scalability Build robust systems for data quality assurance and validation at scale Collaborate with research teams to implement novel data processing architectures Build and operate end-to-end data pipelines that turn raw web-scale corpora into training-ready datasets You may be a good fit if you have: 5+ YOE outside of internships Strong software engineering skills with experience building high-throughput fault-tolerant distributed systems Hands-on experience with distributed computing frameworks, particularly Apache Spark Excellent problem-solving skills and attention to detail Strong communication skills and ability to work in a collaborative environment Advanced degree in Computer Science or related field Experience with language model training infrastructure Background in Data Infrastructure, MLOps, or ML infrastructure Strong candidates may have: Have significant experience building high-throughput fault-tolerant distributed systems Expertise with Python and Rust Passionate about system reliability and performance Are comfortable working with ambiguous requirements and evolving specifications Take ownership of problems and drive solutions independently Are excited about contributing to the development of safe and ethical AI systems Can balance technical excellence with practical delivery Are eager to learn about machine learning research and its infrastructure requirements Sample Projects Designing and implementing distributed computing architecture for web-scale data processing Building scalable infrastructure for model training data preparation Developing fault-tolerant distributed processing systems Implementing new infrastructure components based on research requirements The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Berlin, Germany Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. Speed is something we fight for every day at Fin, and we believe Berlin is built for people who share that instinct. We are drawn to Berlin by its rare blend of deep technical talent and rich creative culture – all within a vibrant, globally connected city that’s close to our R&D hubs in Dublin and London. It’s a place where the best of the best technical talent thrive, and where people from around the world are eager to relocate and build ambitious products. Our ambition is to hire 100 people in Berlin over the year ahead across engineering, AI, data science, product, and design. We believe this is the most exciting time to join, be the founding R&D talent in the region and make a lasting impact as we build the world's number one customer agent! What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Identify areas where ML can create value for our customers Identify the right ML framing of product problems Working with teammates and Product and Design stakeholders Conduct exploratory data analysis and research Deeply understand the problem area Research and identify the right algorithms and tools Being pragmatic, but innovating right to the cutting-edge when needed Perform offline evaluation to gather evidence an algorithm will work Work with engineers to bring prototypes to production Plan, measure & socialize learnings to inform iteration Partner deeply with the rest of team, and others, to build excellent ML products What skills might I need? Broad applied machine learning knowledge 3-5 years applied ML experience Practical stats knowledge (experiment design, dealing with confounding etc) Intermediate programming skills Strong communication skills, both within engineering teams and across disciplines. Comfort with ambiguity Typically have advanced education in ML or related field (e.g. MSc) Scientific thinking skills Bonus skills & attributes Track record shipping ML products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Visualization, data skills, SQL, matplotlib, etc. Benefits We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! Competitive salary, annual bonus and equity Regular compensation reviews - we reward great work! Generous paid time off above statutory minimum Generous family leave (maternity, paternity), to let you spend valuable time with your loved ones Hybrid working MacBooks are our standard, but we also offer Windows for certain roles when needed. Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated Fun events for employees, friends, and family! Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Location: Ukraine; Poland; Armenia; Georgia; Moldova Intetics Inc. is a global technology company providing custom software application development, distributed professional teams, software product quality assessment, and “all-things-digital” solutions. Based on its proprietary business model of Remote In-Sourcing® , advanced Technical Debt Reduction Platform (TETRA™) , and measurable quality management platform ( Predictive Software Engineering ), Intetics enables clients to achieve measurable business results. Position Details Position: BI Developer / Apache Superset Dashboard Engineer Level: Mid to Senior Technologies: Apache Superset, Elasticsearch Query DSL, SQL (Postgres/Oracle), Unix/Linux, Jira Workload: 700 hrs/year Location: Remote — work from anywhere English level: Advanced Education: Technical degree Role Description We are seeking a BI Developer / Apache Superset Dashboard Engineer to design, build, and optimize data visualizations and KPI dashboards in Apache Superset. This role involves transforming complex datasets into clear, actionable insights through interactive dashboards and reports, working closely with data engineers and analysts. You will ensure high-quality data visualization aligned with business objectives and contribute to Agile delivery in a fast-paced environment. Role Description We are seeking a BI Developer / Apache Superset Dashboard Engineer to design, build, and optimize data visualizations and KPI dashboards in Apache Superset . This role involves transforming complex datasets into clear, actionable insights through interactive dashboards and reports, working closely with data engineers and analysts. You will ensure high-quality data visualization aligned with business objectives and contribute to Agile delivery in a fast-paced environment. Requirements Technical Responsibilities and Skills What You’ll Do: Design and develop Apache Superset dashboards for KPIs and data insights. Write and optimize Elasticsearch Query DSL queries. Work extensively with SQL on PostgreSQL and/or Oracle . Operate in Unix/Linux environments for data access and automation tasks. Deliver work tracked through Jira , following Agile methodology. What We’re Looking For: ≥ 3 years of Apache Superset (dashboard & KPI design). ≥ 3 years of Elasticsearch Query DSL . ≥ 3 years of SQL on Postgres and/or Oracle . ≥ 3 years in Unix/Linux environments . ≥ 3 years of Jira-tracked Agile delivery . Advanced English and a technical degree . Nice-to-Have / Bonus: Superset certification . Background in UX/UI or data visualization . Experience developing custom Superset plugins or visualizations .

Location: Berlin, Germany Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? As a Staff Engineer, you will be a leader within the team and a strong contributor to the engineering organization. You will build both back-end and front-end systems, and work closely with designers, product managers, researchers, and data analysts. You will coach and mentor other engineers and partner closely with the Engineering Manager to develop the team and to devise technical strategy. Learn more about our engineering culture at intercom.engineering What will I be doing? As an experienced engineer you will: Contribute to our technical architecture as we grow. We scale to service requests from all our customers’ customers. We’re growing and so are they. Care about agility as much you care for scalability and availability. Continuous deployment keeps us focused on incremental releases. Even our biggest technical achievements roll out piece by piece, feature flagged out of sight. Contribute to all phases of software development including ideation, prototyping, design and implementation. This role has a mix of both hands-on development as well as lead/architecture work. Build using the best tools in the industry. We invest heavily in AI-powered developer tools that remove friction and help you focus on solving meaningful problems. Play an active role in hiring, mentoring and career development of other engineers Raise the bar for technical standards, performance, reliability, and operational excellence What skills do I need? Ideally, you’ve built an exciting SaaS product in your previous roles and loved the satisfaction that comes with knowing that people around the world are using something you’ve created Significant, demonstrated impact that your work has had on the product and/or the teams Deep knowledge of a high-level programming language (for example, Ruby, Python, Perl etc.) but it doesn’t need to be a language that we use here! Great people are effective and learn what we use quickly (or introduce us to better ways of working) You will have experience with Distributed systems 2+ years of experience as the primary technical leader for a team Experience collaborating directly with product teams and designers, and a proven track record of delivering value to customers or users. Engineers at Fin are pragmatists who work closely with others on cross-disciplinary teams and have a strong sense of product strategy. #LI-Hybrid Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Location: Lagos, Nigeria Eram Talent, a leading Talent Acquisition Company, is seeking a qualified and experienced HV Technician - Electrical to join a prestigious company in the industry. As a HV Technician, you will be responsible for working with high voltage electrical systems, ensuring that maintenance, troubleshooting, and repairs are conducted safely and efficiently. This role offers an exciting opportunity to contribute to important projects and be part of a team of skilled professionals. If selected, this opportunity would be onsite at Saudi Arabia. Responsibilities Install, maintain, and repair high voltage electrical equipment and systems. Conduct preventive maintenance and inspections on electrical systems to enhance reliability and performance. Troubleshoot electrical faults and provide effective solutions to restore system functionality. Ensure compliance with safety regulations and standards while working on high voltage systems. Coordinate with other team members and departments to minimize downtime during maintenance activities. Maintain accurate records of maintenance activities, equipment status, and inspection reports. Stay updated with advancements in high voltage technology and industry best practices. Participate in safety training and promote a culture of safety in the workplace. Requirements Technical diploma or certification in Electrical Engineering or a related field. Minimum of 5 years of experience working with high voltage electrical systems. Strong knowledge of electrical safety protocols and high voltage regulations. Experience with the installation and maintenance of substations, transformers, and switchgears. Excellent troubleshooting skills and ability to interpret electrical schematics. Strong attention to detail and commitment to safety standards. Good communication and organizational skills. Ability to work effectively both independently and as part of a team. Willingness to work in various conditions and on-call as required.

Location: Uzbekistan, . P.I. Works is the first company in the world to automate the management of a commercial 5G network. Our automated network management products and services empower mobile operators to accelerate network transformation and to drive network quality and efficiency on the path to 5G. These solutions have been deployed across 84 mobile network operators in 58 countries around the world. Our product support team based in Istanbul provides exceptional service to customers worldwide on our platform, products and solutions. Our team boasts some of the brightest technologists and engineers in the industry, who thrive on solving customer issues and ensuring the highest quality of service. As a member of the Global services and product support team, you will have the ability to work independently or as part of a team with some of P.I. Work’s most strategic customers to drive their success.  Being a highly motivated individual as well as a self-learner, possessing strong customer service and technical and analytical skills; and being someone who welcomes challenges will help you to achieve in your role. As part of the role definition, you will: Provide exceptional service to our customers worldwide Actively communicate with customers on questions/issues related to our products and solutions Go above and beyond our service level agreements to pro-actively diagnose and resolve issues Collaborate with customers on deployment and provide support for upgrades, new features and fixes Collaborate with team members, share knowledge, lessons learned, document best practices through active participation in team meetings and trainings Collaborate with project teams on installation, configuration, testing and integration of our solutions. Required Experience and Skills: Basic to intermediate knowledge of database architecture and good command on SQL Good understanding of programming in C++/C#/Java and .NET framework is an asset Good understanding of one or more OSS products is an asset Technical understanding of 2G/3G/4G mobile technologies, including RAN standards, architectures, protocols, and services is an asset. Passionate and self-motivated individual capable of troubleshooting and solving complex customer issues in a fast-paced, dynamic environment. Excellent communication and interpersonal skills in both verbal and written English.