Location: London, UK
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:
You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our
Responsible Scaling Policy
), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team.
Our blog
provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. For the London team, we are opportunistically hiring for the following research areas:
AI Control:
Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios.
Alignment Stress-testing
:
Creating
model organisms of misalignment
to improve our empirical understanding of how alignment failures might arise.
Note: Currently, the team's hub is in San Francisco, so we require all candidates to be based at least 25% in London
and
travel to San Francisco occasionally. Additionally, we are prioritizing growing our San Francisco teams, so you may not hear back on your application to the London team unless we see an unusually strong fit. For this role, we conduct all interviews in Python.
Representative Projects:
Testing the robustness of our safety techniques by training language models to subvert our safety techniques, and seeing how effective they are at subverting our interventions.
Run multi-agent reinforcement learning experiments to test out techniques like
AI Debate
.
Build tooling to efficiently evaluate the effectiveness of novel LLM-generated jailbreaks.
Write scripts and prompts to efficiently produce evaluation questions to test models’ reasoning abilities in safety-relevant contexts.
Contribute ideas, figures, and writing to research papers, blog posts, and talks.
Run experiments that feed into key AI safety efforts at Anthropic, like the design and implementation of our
Responsible Scaling Policy
.
You may be a good fit if you:
Have significant software, ML, or research engineering experience
Have some experience contributing to empirical AI research projects
Have some familiarity with technical AI safety research
Prefer fast-moving collaborative projects to extensive solo efforts
Pick up slack, even if it goes outside your job description
Care about the impacts of AI
Strong candidates may also:
Have experience authoring research papers in machine learning, NLP, or AI safety
Have experience with LLMs
Have experience with reinforcement learning
Have experience with Kubernetes clusters and complex shared codebases
Candidates need not have:
100% of the skills needed to perform the job
Formal certifications or education credentials
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:
£260,000
—
£370,000 GBP
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.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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: Belgrade; London; Berlin
Workplace: Hybrid
Perplexity is seeking an experienced Machine Learning Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking.
Responsibilities
- Relentlessly push search quality forward—through models, data, tools, or any other leverage available
- Architect and build core components of our search platform and model stack
- Train and evaluate retrieval, ranking and classification models, including LLMs
- Deploy models - from boosting to LLMs - in a scalable and performant way
- Build and optimize RAG pipelines for grounding and answer generation
- Collaborate with Data, AI, Infrastructure and Product teams to ensure fast and high quality delivery
Qualifications
- Deep understanding of search and retrieval systems, including quality evaluation principles and metrics
- Proven track record with large-scale search or recommender systems
- Self-driven, with a strong sense of ownership and execution
- Minimum of 5 years of working on search or recsys-related projects
Location: Belgrade; London; Berlin
Workplace: Hybrid
Perplexity is seeking an experienced Machine Learning Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking.
Responsibilities
- Relentlessly push search quality forward—through models, data, tools, or any other leverage available
- Architect and build core components of our search platform and model stack
- Train and evaluate retrieval, ranking and classification models, including LLMs
- Deploy models - from boosting to LLMs - in a scalable and performant way
- Build and optimize RAG pipelines for grounding and answer generation
- Collaborate with Data, AI, Infrastructure and Product teams to ensure fast and high quality delivery
Qualifications
- Deep understanding of search and retrieval systems, including quality evaluation principles and metrics
- Proven track record with large-scale search or recommender systems
- Self-driven, with a strong sense of ownership and execution
- Minimum of 5 years of working on search or recsys-related projects
ГибридBelgrade; London; Berlin
Не хотите искать каждый день?
Настройте подбор один раз, и подходящие вакансии будут сами приходить в Telegram.
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Workplace: remote
Location
:
Quantori is an international team: we have colleagues who work not only from office but also remotely from all over the world.
Responsibilities
:
Ability to collaborate closely with machine learning engineers and data scientists to refine AI models, develop robust model embeddings, and optimize prompts for accuracy, performance, and cost-efficiency
Develop and optimize AI agent systems, including multi-agent orchestration and tool integration
Implement and iterate on RAG pipelines, evaluation frameworks, and LLM-powered data processing solutions
Maintain and enhance applications and solutions on Python
What we expect
:
A solid knowledge of Python, with experience in writing clean, efficient, and maintainable code
Ability to design and develop autonomous agents using frameworks such as LangGraph/CrewAI/OpenAI Agents SDK, enabling intelligent decision-making and task automation
Experience in rapid prototyping using large language models (LLMs), vector databases, and knowledge graphs to explore and implement new AI-driven capabilities
Expertise in retrieval-augmented generation (RAG) workflows and document retrieval techniques to enhance content relevance
Hands-on experience working with large-scale language models, such as GPT/Claude/Gemini/Qwen, along with a solid understanding of prompt engineering, embedding techniques
Familiarity with the Model Context Protocol (MCP) for connecting LLM agents to external tools and data sources
Experience in rapid prototyping of AI-driven capabilities using LLMs, embeddings, and structured/unstructured data sources
Experience with code generation and AI-assisted development tools (Claude Code, GitHub Copilot, Cursor, Codex)
Strong written and spoken English communication skills (B2)
Nice to have
:
Experience with Python frameworks such as Django, Flask, or FastAPI
Proficiency in SQL for working with structured databases, querying data, and optimizing database performance
Familiarity with platforms Dataiku, Snowflake, Tableau, Streamlit, Artifactory, dbt
Hands-on experience with NLP deep learning frameworks such as PyTorch, TensorFlow, and Transformers
Familiarity with graph RAG approaches (Microsoft GraphRAG, LightRAG, or Neo4j-based solutions)
Understanding AI cost optimization: model routing, caching strategies (semantic caching), prompt compression, and token management
We offer
:
Competitive compensation
Remote or office work
Flexible working hours
A team with excellent tech expertise
УдалённоseniorQuantori is an international team: we have colleagues who work not only from office but also remotely from all over the world
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?
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?
Play an active role in hiring, mentoring and career development of other engineers
Raise the bar for technical standards, performance, reliability, and operational excellence
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?
5-8 years applied ML experience
Previous background in a senior/staff role (data science, software development or academic)
Significant, demonstrated impact that your work has had on the product and/or the teams
Strong programming skills
Experience as the primary technical leader for a team
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.
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: Bremen, Germany
Our mission
Constructor’s mission is to enable all educational organisations to provide high-quality digital education to 10x people with 10x efficiency.
With strong expertise in machine intelligence and data science, Constructor’s all-in-one platform for education and research addresses today’s pressing educational challenges: access inequality, tech clutter, and low engagement of students.
Please send your resume in English only.
Interns are NOT eligible for equipment and other benefits as the position is temporary.
The Reality
The frontier models are converging into commodities; the engine is no longer the differentiator. The scarcity in 2026 is not the model.
We are not looking for people to fine-tune Llama on toy datasets or write "better prompts." We are building the runtime systems that turn probabilistic token generation into reliable workers that finish 50-step tasks without spiraling. We are solving the math of multi-step reliability through engineering, not wishful thinking.
What You Will Solve
You will work on the
Agentic Harness
, treating the LLM as a component within a larger, deterministic control system. Your research will focus on:
Architecting loops that survive error accumulation. You will build verification layers that force the agent to recognize its own hallucinations and self-correct.
You will implement systems where the agent compiles its own constraints and the harness enforces them via constrained decoding or external execution.
You will optimise KV-cache hit rates and design "restorable compression" strategies to prevent attention decay.
Who We Are Looking For
We are looking for
systems thinkers
who happen to know ML, not the other way around.
You know that a demo is not a product. You are interested in the "boring" engineering: state machines, retries, idempotency, serialisation — that actually makes agents work.
You are comfortable working with the raw output of the model and building robust software in Python or Rust around it.
You understand why dynamic tool loading destroys inference economics. You prefer deterministic guardrails over "prompting it to be nicer."
You are willing to read a 500-line trace of a failed agent loop to find the exact moment the context drifted. You care about the "last mile" of reliability.
What We Offer For Interns:
Internship Duration: from 2 months or more
Type of internship:
100% remote
or hybrid
in the office in Bremen (GER), Sofia (BG), Belgrade (SRB), Istanbul (TR), Sakarya (TR), Singapore (SGD)
What We Offer
💻 Choice of work equipment (e.g., laptop, monitor, etc.)
🇬🇧 English classes (iTalki – $130 monthly)
⏰ Flexible schedule (we usually work between 09:00/10:00 and 18:00/19:00)
👶 Newborn bonus (€500 per child)
🧠 Patent remuneration
🌴 Paid leave
🧑💻 Remote work in locations without our offices
Hybrid work in locations with offices (2 days in-office, 3 days remote)
Constructor
fosters equal opportunity for people of all backgrounds and identities. We are led by a gender-balanced board committed to building a diverse and inclusive organisation where everyone can become their best self. We do not discriminate based on age, disability, gender identity, sexual orientation, ethnicity, race, religion or belief, parental and family status, or other protected characteristics. We welcome applications from women, men and non-binary candidates of all ethnicities and socio-economic backgrounds. We encourage people belonging to underrepresented groups to apply.
Location: Paris; San Francisco; London; New York; 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:
Contribute in and provide strong support for model training pipelines, ship state of the art models to production, and bridge the gap between research and production. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and supporting our research effort depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work.
Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role.
Key Responsibilities:
- Design and write high-performant and scalable software for training.
- Improve our training setup from an infrastructure and codebase performance standpoint.
- Craft and implement tools to speed up our training cycles and improve the overall efficacy of our training infrastructure
- Research, implement, and experiment with ideas on our supercompute and data infrastructure.
- Learn from and work with the best researchers in the field.
Qualifications:
- Extremely strong software engineering skills.
- Proficiency in Python and related ML frameworks such as JAX, Pytorch and XLA/MLIR.
- Experience with distributed training infrastructures (Kubernetes, Slurm) and associated frameworks (Ray)
- Experience using large-scale distributed training strategies.
- Hands on experience on training large model at scale and having contributed to the tooling and/or setup of the training infrastructure
- Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).
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: London; New York; Paris; Toronto; Montreal
Workplace: Hybrid
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:
As a Performance Engineer in the Pre-Training team you will be responsible for optimizing the performance of our advanced language models and systems. Their primary focus is on improving key model training metrics, such as training throughput, ensuring high accelerator utilization.
The team combines expertise in software engineering, machine learning, and low-level kernel design and development to design robust systems and enhance model performance. You will work on identifying and removing performance bottlenecks, develop cutting-edge training and profiling tools to help Cohere's mission of providing efficient and reliable language understanding and generation capabilities and drive innovation in the field of natural language processing.
Note: We have offices in London, Toronto, New York and San Francisco, but we’re also remote-friendly! This team operates primarily between ET to CET time zones, so we’re seeking candidates in locations that align with these hours for effective collaboration.
Key Responsibilities:
- Design and write high-performant and scalable software for training.
- Understand architectural modifications and design choices and their effects on training throughput and quality.
- Write low-level CUDA, triton kernels to squeeze every last bit of performance from our accelerators.
- Research, implement, and experiment with ideas on our supercompute and data infrastructure.
- Learn from and work with the best researchers in the field.
Qualifications:
- Extremely strong software engineering skills.
- Proficiency in Python and related ML frameworks such as JAX, Pytorch and XLA/MLIR.
- Experience writing kernels for GPUs using CUDA, triton, etc
- Experience using large-scale distributed training strategies.
- Familiarity with autoregressive sequence models, such as Transformers.
Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).
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: 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?
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.
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; New York; Paris; 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:
At Cohere, we believe in the power of multimodal AI to revolutionise the way we interact with technology. Our engineering teams push the boundaries of what's possible, and we're looking for talented individuals to join us on this exciting journey. With an exceptional ratio of compute resources to engineers, we provide an ideal environment for you to explore, innovate and shape the future of AI.
On July 31st 2025, Cohere's Multimodal team Introduced Command A Vision: Multimodal AI Built for Business. At release our new flagship vision-language model:
● Consistently outperforms major models like Llama 4 Maverick, Mistral Medium/Pixtral Large, and GPT4.1
● 83.1% average benchmark (73.5% MathVista, 90.9% ChartQA...)
● Built for the real world - 112B parameters running on just 2 GPUs
● Open weights live on HuggingFace
With a focused team, breakthrough performance doesn't require breakthrough compute. Focus on the things that matter, and join the team. This role is perfect for you if you:
- Have a deep passion for machine learning and its potential to impact various industries through multimodal applications.
- Enjoy tuning and optimising large multimodal models, and have experience building evaluations to measure their performance.
- Are comfortable diving into complex ML codebases to identify and resolve issues, ensuring the smooth operation of our systems.
- Thrive in a fast-paced, technically challenging environment, where you can contribute your innovative ideas and solutions.
- Have a history of delivering creative, practical solutions to real-world problems, demonstrating your ability to think outside the box.
Key Responsibilities:
- Design and develop cutting-edge multimodal AI systems, integrating various modalities such as text, speech, and vision.
- Conduct research and experiments on our advanced compute infrastructure, exploring novel ideas in multimodal representation learning, transfer learning, and more.
- Collaborate closely with our world-class teams, learning from and contributing to their expertise in the field.
Qualifications:
- Possess exceptional software engineering skills, with a proven track record of building robust and scalable systems.
- Have a strong command of Python and are well-versed in popular deep learning frameworks like JAX, PyTorch, and TensorFlow, with an understanding of their multimodal capabilities.
- Knowledge of distributed training strategies, especially for large-scale multimodal models.
- Familiarity with autoregressive models, particularly their application in multimodal tasks such as image or video captioning, speech-to-text generation.
- Bonus: Publications in top-tier venues demonstrating your expertise in multimodal AI research.
- Bonus: Experience in writing efficient GPU kernels using CUDA, optimising performance for multimodal tasks.
If you're excited about the potential of multimodal AI and want to be at the forefront of this rapidly evolving field, we want to hear from you! Join us at Cohere and be a part of a diverse, remote-friendly team that's changing the world of AI.
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: London; San Francisco; New York; Paris; 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!
Please note that this is not a live role. We are grateful for your enthusiasm and interest in Cohere and encourage you to submit your resume for future consideration. Should a suitable position become available, we will review your application and reach out to discuss potential opportunities.
Role Overview:
Design and implement novel research ideas, ship state of the art models to production, and maintain deep connections to academia. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and conducting research depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work.
Please Note: We have offices in Toronto, London, Paris, San Francisco and New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role.
Key responsibilities:
- Design, build and scale AI systems for serving our users.
- Research, implement, and experiment with ideas on our supercompute and data infrastructure.
- Learn from and work with the best researchers in the field.
Qualifications:
- Extremely strong software engineering skills.
- Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR.
- Experience writing kernels for GPUs using CUDA.
- Experience using large-scale distributed training strategies.
- Familiarity with autoregressive sequence models, such as Transformers.
- Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).
* This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We have a wide variety of backgrounds at Cohere.
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: Remote
Workplace: Remote
We are building AI to simulate the world through merging art and science.
We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world.
World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached.
Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you.
*Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers.
ABOUT THE ROLE
Building general world models — systems that understand and simulate reality across tasks, modalities, and domains — demands training data that is as rich and varied as the real world itself. We’re looking for Research Engineers to own the data behind our models: what they learn from, how well they learn it, and what new capabilities that unlocks. You will design datasets, run modeling experiments, and build the infrastructure to generate and curate data at scale — directly shaping what our models can do, with applications ranging from creative tools to robotics.
WHAT YOU'LL DO
- Design multimodal, multitask datasets that teach world models new capabilities — deciding what data to collect, generate, or curate and measuring its effect on model behavior
- Run controlled training experiments to understand how data composition drives model performance across tasks and domains
- Build and operate large-scale pipelines for synthetic data generation, filtering, and quality control
- Define evaluations and benchmarks that measure whether our models are actually improving at the things that matter
- Partner with product and creative teams to translate target behaviors and capabilities into concrete data strategies
WHAT YOU'LL NEED
- 4+ years of experience in machine learning, bonus points for data-centric approaches
- Experience with large multimodal datasets and generative models (video, image, or multimodal)
- Deep intuition for how data composition and quality translate to model capabilities
- Comfort working across the full research stack: data analysis, dataset creation, model training, evaluation, and back again
- Proficiency with at least one ML framework (e.g. PyTorch, JAX) and distributed compute tools (e.g. Ray, Kubernetes)
- Excitement about building AI that simulates the world
Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide.
There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range.
Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates.
WORKING AT RUNWAY
Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you.
We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply.
More about Runway
- Universal World Simulator https://runwayml.com/world-simulator.html
- GWM-1 https://runwayml.com/research/introducing-runway-gwm-1
- Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5
- General World Models https://runwayml.com/research/introducing-general-world-models
- Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section
- Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section
- Runway Studios https://runwayml.com/studios
We're excited to be recognized as a best place to work:
Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024
Location: Tel Aviv
DRW
is a technology-driven, diversified principal trading firm. We trade our own capital at our own risk, across a broad range of asset classes, instruments and strategies, in financial markets around the world. As the markets have evolved over the past 25 years, so has DRW – maximizing opportunities to include real estate, cryptoassets and venture capital. With over 1,000 employees at our Chicago headquarters and offices around the world, we work together to solve complex problems, challenge consensus and deliver meaningful results. It’s a place of high expectations, deep curiosity and thoughtful collaboration
DRW
is looking for highly skilled
Machine Learning Engineer
for an Algorithmic Trading Research Group in Tel Aviv. DRW office is located at the TLV expo center, right next to TLV University train station and offers highly competitive compensation packages.
As a
Machine Learning Engineer
, you will be an integral member of an algorithmic trading team comprised of experienced technologists and quantitative researchers. Your team will work closely to solve challenging technical problems and contribute to our full tech stack, from hardware and software development to grid computing. You will be surrounded by cutting edge technology, offered training and continuing education opportunities, and given immediate responsibility. We are looking for creative technologists, natural programmers, and disciplined engineers eager to develop new technologies that directly impact our business.
How you will make an impact:
Build infrastructure for running Machine Learning algorithms on big data.
Optimize Machine Learning algorithms to run under latency constraints.
Parallelize Machine Learning algorithms to run on a parallel compute grid.
Build software for data acquisition and cleaning that can handle hundreds of terabytes of data.
Build data visualization tools for feature exploration and model verification.
Integrate Machine Leaning algorithms into trading strategies simulations to verify end to end performance improvements.
Contribute to technological innovation through exploration of cutting-edge hardware, software, and methods.
As an active member of the research team you will have an impact on the technological direction and the analysis of trade-offs between complexity and performance.
What you bring to the team:
MSc-Bsc in Computer Science, Computer Engineering, or related field.
5+ years of software development experience in modern C++ and Python.
A strong understanding of object-oriented design, data structures, and algorithms.
Ability to advise and collaborate with researchers on software engineering tools and practices.
A solid foundation in programming with the ability to think, communicate, and code clearly.
Skills in numerical computing, machine learning, and visual intelligence.
Demonstrated ability to produce algorithmic code in a fast-paced environment.
For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at
https://drw.com/privacy-notice
.
California residents, please review the California Privacy Notice for information about certain legal rights at
https://drw.com/california-privacy-notice
.
#LI-GV1 #LI-Onsite
Location: Riyad, Saudi Arabia
As an AI / Computer Vision Engineer at Müller's Solutions, you will have the opportunity to work on cutting-edge projects that leverage artificial intelligence and computer vision technologies. You will collaborate with cross-functional teams to develop innovative solutions that solve complex business challenges using AI and computer vision algorithms and techniques.
Responsibilities:
Design and develop AI and computer vision solutions for various industries and use cases.
Implement and optimize computer vision algorithms for object detection, image recognition, and image segmentation.
Train and fine-tune machine learning models using large datasets.
Collect and preprocess data for training and validation purposes.
Integrate AI and computer vision solutions into existing systems and platforms.
Perform testing and debugging of AI and computer vision models and systems.
Stay current with the latest advancements in AI and computer vision technologies.
Building Computer Vision AI models
including all pre-processing and post-
processing
Ownership of the Entire Solution
Daily Updates
Knowledge sharing
Requirements
Requirements:
Bachelor's degree in Computer Science, Engineering, or a related field.
Proven experience in AI and computer vision development.
HANDS ON PYTHON AND DATABASES( SQL AND
NOSQL), Open CV
COMFORTABLE WITH LINUX
Experience with data preprocessing and data augmentation techniques.
Knowledge of software development practices and version control systems.
Excellent problem-solving and analytical skills.
Ability to work independently and in a team environment.
Good communication and collaboration skills.
Location: Москва
Мы команда GigaChat - создаём и развиваем core-технологию генеративной языковой модели. Она может писать тексты, создавать изображения и даже код на Python. Она умеет отвечать на вопросы, вести диалог, сочинять стихи и рассказы, придумывать идеи для бизнеса, писать письма и многое другое.
Приглашаем в команду талантливого NLP Enginner, с которым мы будем вместе усовершенствовать и развивать GigaChat. В работе будет очень много креативности и придумывания новых подходов. Для всех этих экспериментов у нас есть кластер с большим числом A/H 100'ых.
Обязанности
* довести качество до ChatGPT на русском и дальше обогнать его
* помогать решать бизнес-задачи с помощью нашей технологии сначала для внутренних клиентов в Сбере, а потом и внешним
* придумывать и внедрять новые применения для LLM
* помогать выводить в прод все, что мы обучим
* постоянно держаться up-to-date со свежими статьями.
Требования
* Python, алгоритмы, математика
* знания в DL, опыт обучения просто моделей и больших моделей
* опыт обучения моделей для продакшен
* понимание текущего состояния эволюции больших LLM's
* C++ & CUDA
* публикации.
Условия
* комфортный современный офис рядом с м. Кутузовская
* возможность выбрать удобный график – офис/гибрид
* ежегодный пересмотр зарплаты и годовая премия
* корпоративный спортзал и зоны отдыха
* более 400 образовательных программ СберУниверситета для профессионального и карьерного развития
* расширенный ДМС, льготное страхование для семьи
* ипотека для сотрудников выгоднее до 4%
* бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров
* вознаграждение за рекомендацию друзей в команду Сбера.
Location: Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY
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:
We are looking for Research Engineers to help us redesign how Claude interacts with external data sources. Many of the paradigms for how data and knowledge bases are organized assume human consumers and constraints. This is no longer true in a world of LLMs! Your job will be to design new architectures for how information is organized, and train language models to optimally use those architectures.
Responsibilities:
Designing and implementing from scratch new information architecture strategies
Performing finetuning and reinforcement learning to teach language models how to interact with new information architectures
Building “hard” knowledge base eval sets to help identify failure modes of how language models work with external data
Designing and evaluating advanced agentic search capabilities.
You may be a good fit if you:
Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using
Have good machine learning research experience
Have experience developing software that utilizes Large Language Models such as Claude
Are results-oriented, with a bias towards flexibility and impact
Pick up slack, even if it goes outside your job description
Enjoy pair programming (we love to pair!)
Want to partner with world-class ML researchers to develop new LLM capabilities
Care about the societal impacts of your work
Have clear written and verbal communication
Strong candidates will also have experience with:
Collaborating with product teams to quickly prototype and deliver innovative solutions
Building complex agentic systems that utilize LLMs
Developing scalable distributed information retrieval systems, such as search engines, knowledge graphs, RAG, indexing, ranking, query understanding, and distributed data processing
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.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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 | New York City, NY | Seattle, WA
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:
Multi-Agent systems are becoming an increasingly important part of how AI is deployed, whether via fast small-model subagents inside a product, or
large groups of agents
solving
very large problems
. Training Claude to be maximally effective and safe within large groups is a challenging new area of reinforcement learning, and represents a new axis for scaling test time compute.
We are looking for researchers who have experience training multi-agent systems at the largest scale and an appreciation for the incentives and mechanism design that come into play.
Responsibilities:
Help create and optimize environments and data for model training that maximize Claude’s performance or ease of use on agentic tasks
Ideate, develop, and compare the performance of different agent harness configurations (eg memory, context management, communication architectures for agents)
Design and implement rigorous quantitative benchmarks for large scale agentic tasks
Work with our product org to find solutions to our most vexing challenges in applying agents to our products
You may be a good fit if you:
Have experience with large-scale RL on language models
Have experience training multi-agent systems
Enjoy going deeply into the roots of a problem and understanding its foundations, rather than its surface.
Have good communication skills and an interest in working with other researchers on difficult tasks
Have a passion for making powerful technology safe and societally beneficial
Are excited for a mission-driven org with fast-paced, impactful work
Representative projects:
Design and build reinforcement learning environments to train groups of Claudes how to solve problems together efficiently
Design and build agent affordances that unlock new capabilities and scales of agents, while keeping the Bitter Lesson in mind
Design and build a novel eval that measures how large teams of agents interact in groups to solve problems
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.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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; Remote; Toronto; New York; Montreal; Seattle
Workplace: Hybrid
ABOUT BASETEN
Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.
THE ROLE
As a Forward Deployed Engineer at Baseten, you will partner directly with customers to architect, build, and deploy high-scale production AI applications on Baseten’s platform. You’ll own the journey with customers from initial exploration to production deployment, translating ambiguous business goals into reliable, observable services with clear quality, latency, and cost outcomes.
This role is a great fit for entrepreneurial engineers who want a front-row view into how modern companies adopt AI at scale and who enjoy working across product, software development, performance engineering, and customer-facing implementations.
To be clear, this is an engineering role with hands-on coding and software development that also includes aspects of product management, technical customer success, and pre-sales solution engineering mixed in.
EXAMPLE INITIATIVES
Take a look at these blog posts written by members of our Forward Deployed Engineering team:
- Forward Deployed Engineering on the frontier of AI https://www.baseten.co/blog/forward-deployed-engineering/
- The fastest, most accurate Whisper transcription https://www.baseten.co/blog/the-fastest-most-accurate-and-cost-efficient-whisper-transcription/
- Deploy production-ready model servers from Docker images https://www.baseten.co/blog/deploy-production-model-servers-from-docker-images/
- Deploy custom ComfyUI workflows as APIs https://www.baseten.co/blog/deploying-custom-comfyui-workflows-as-apis/
RESPONSIBILITIES
- Develop and maintain software systems and product features using one or more general-purpose programming languages in a production-level environment, with a preference for Python due to its relevance in ML projects.
- Drive customer impact by designing, implementing, and deploying Baseten solutions end-to-end (problem framing → evaluation → production deployment → monitoring). This involves working with customers’ engineering teams at every stage of the customer journey including: sales, implementation, and expansion.
- Deliver with velocity: turn vague objectives into clear specs and well-defined PoCs so we can rapidly ship well-tested services and outcomes for our customers
- Optimize and enhance AI/ML projects, contributing to the continuous improvement of our technical stack. This includes developing features and PRDs with other engineering and product orgs.
- Own products and customer projects end-to-end, functioning as both an engineer, project manager, and product manager, with a focus on user empathy, project specification, and end-to-end execution.
- Navigate ambiguity and exercise good judgment on tradeoffs and tools needed to solve problems, avoiding unnecessary complexity.
- Demonstrate pride, ownership, and accountability for your work, expecting the same from your teammates.
REQUIREMENTS
- Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field.
- 2+ years of professional work experience in a fast-paced, high-growth environment.
- Demonstrated experience with one or more general-purpose programming languages in a production-level environment, with a strong preference for Python.
- Familiarity with AI/ML pipelines and the lifecycle of ML model development and deployment.
- Strong communication skills, particularly on complex technical topics.
- Experience in building or optimizing AI/ML projects is highly valued.
BENEFITS
- Competitive compensation, including meaningful equity
- (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
- Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
- Paid parental leave
- Fertility and family-building stipend through Carrot
- (U.S. only) Company-facilitated 401(k)
- Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
Dublin, Ireland
СтажёрBremen, Germany; We welcome applications from women, men and non-binary candidates of all ethnicities and socio-economic backgrounds
УдалённоParis; San Francisco; London; New York; Toronto; Montreal; 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; We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities
ГибридLondon; New York; Paris; Toronto; Montreal; This team operates primarily between ET to CET time zones, so we’re seeking candidates in locations that align with these hours for effective collaboration; 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; We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities
seniorDublin, Ireland
УдалённоseniorSan Francisco; New York; Paris; Toronto; Montreal; 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; We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities
УдалённоLondon; San Francisco; New York; Paris; Toronto; Montreal; 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; We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities
УдалённоСША; Lastly, the provided range is the expected salary for candidates in the U.S
Tel Aviv
УдалённоRemote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY
San Francisco, CA | New York City, NY | Seattle, WA
ГибридSan Francisco; Remote; Toronto; New York; Montreal; Seattle