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Location: London Perplexity is looking for a Search Machine Learning Engineer Intern to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. You will work closely with experienced engineers to improve search quality, experiment with new models, and ship features that directly impact how users search and discover information. Internship program: 12 - 24 weeks, full-time, in-person in the London office. Responsibilities: - Contribute to experiments that improve search quality through better models, data usage, and evaluation tools, under the guidance of senior engineers. - Design and implement components of the search platform and model stack, including retrieval, ranking, and classification models. - Train evaluating models (including LLM-based approaches) for retrieval, ranking, and classification tasks. - Support deployment and monitoring of search and ranking models in a scalable and performant way. - Help build and iterate on RAG pipelines for grounding and answer generation. - Collaborate with Data, AI, Infrastructure and Product teams to deliver improvements quickly and learn best practices in production ML. Qualifications: - Strong foundation in machine learning and statistics, with coursework or projects related to information retrieval, ranking, or recommender systems. - Experience with Python and common ML frameworks (e.g. PyTorch, TensorFlow, JAX) through academic, open source, or personal projects. - Familiarity with evaluating model quality using offline metrics and/or A/B testing is a plus, but not required. - Previous experience (internships, research, or significant projects) working on search, recommendation, or NLP is a plus, but not required. - Self-driven and curious, with a strong sense of ownership, willingness to learn, and comfort working in a fast-paced environment - Experience with Rust will be a plus

Location: Strava SF Workplace: Hybrid ABOUT STRAVA Strava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts—it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count. Start your journey https://www.strava.com/subscription with Strava today. Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward. We are looking for a Machine Learning Engineer to join the growing AI and Machine Learning team at Strava. This team is responsible for sophisticated machine learning models and systems which provide value to Strava athletes including personalization, recommendations, search, and trust and safety. The team also maintains the ML platform and infrastructure that enables our team to iterate on models quickly and deploy them reliably at scale. This is an important role in the ML team and across Product teams designing, roadmapping, and implementing innovative machine learning algorithms. We value full stack ML engineers who are able to work on all parts of an ML pipeline from model building, evaluation, optimizing performance, and ensuring the scalability and reliability of these production models. We also seek those who can improve the systems and tools behind the ML pipeline to further empower the team. We follow a flexible hybrid model that translates to more than half your time on-site in our San Francisco Office — three days per week. WHAT YOU’LL DO: - Build for a Well Loved Consumer Product: Work at the intersection of AI and fitness to launch and optimize product experiences that will be used by tens of millions of active people worldwide - Own End to End AI Systems: Drive key projects powered by ML on the Strava platform end-to-end, from initial model prototyping to shipping production code to scaling and optimizing inference and deployment - Shape AI at Strava: Be a strong voice on a highly collaborative team with a range of experience levels. Work across teams to deploy ML solutions in multiple surfaces and build out our technical ML capabilities. - Innovate in AI for Fitness: Design and develop novel models and methodologies to take on novel problems that improve athlete experience, including recommendation systems, activity prediction, and personalized insights. - Build from a rich dataset: Explore and use Strava’s extensive unique fitness and geo datasets from millions of users to extract actionable insights, inform product decisions, and optimize existing features YOU WILL BE SUCCESSFUL HERE BY: - Driving innovation with Product in mind: Stay up-to-date with the latest research in machine learning, AI, and related fields. Experiment, advocate and get buy-in for innovative techniques to improve existing products or explore new features that result in step function changes to how we build AI at Strava. - Leading as an Owner: Owning your work end-to-end and being accountable for the outcomes in the projects you drive and landing impact for the business. Ensure the end-to-end system delivers as expected through collaboration with partners. - Analyzing the Data: Work closely with product managers, data scientists, and engineers to find opportunities for applying machine learning to drive business impact and enhance Strava’s features and measure impact. - Collaborating in and across teams: Build relationships, advocate, and communicate with cross-functional partners and product verticals to identify opportunities and bring your technical vision to life. - Raising the ML standard: Help work towards best practices for model development, deployment, and maintenance. - Being passionate about the work you are doing and contributing positively to Strava’s inclusive and collaborative team culture and values WHAT YOU’LL BRING TO THE TEAM: - Have worked on numerous machine learning problems and broken them down into incremental tasks. - Have demonstrated solid interpersonal and communication skills, and collaborative approach to drive business impact across teams. - Have experience building, shipping, and supporting ML models in production at scale. - Have experience with exploratory data analysis and model prototyping, using languages such as Python or R and tools like Scikit learn, Pandas, Numpy, Pytorch, Tensorflow, and Sagemaker. - Have built and worked on data pipelines using large scale data technologies (like Spark, Hadoop, EMR, SQL, and Snowflake). - Are experienced and interested in production ML model operational excellence and best practices, like automated model retraining, performance monitoring, feature logging, and A/B testing. - Have built backend production services on cloud environments like AWS, using languages like (but not limited to) Python, Ruby, Java, Scala, and Go. For information on benefits, please click here. https://docs.google.com/document/d/e/2PACX-1vTkFMPz3eCjd0FgQ28VWnK4d2BEnzGyaSFGwATR-dQdBb9HxZgay6kboqnT0-V-qaBDzSvYIzI76vT5/pub WHY JOIN US? Movement brings us together. At Strava, we’re building the world’s largest community of active people, helping them stay motivated and achieve their goals. Our global team is passionate about making movement fun, meaningful, and accessible to everyone. Whether you’re shaping the technology, growing our community, or driving innovation, your work at Strava makes an impact. When you join Strava, you’re not just joining a company—you’re joining a movement. If you’re ready to bring your energy, ideas, and drive, let’s build something incredible together. Strava builds software that makes the best part of our athletes’ days even better. Just as we’re deeply committed to unlocking their potential, we’re dedicated to providing a world-class, inclusive workplace where our employees can grow and thrive, too. We’re backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we’re expanding in order to exceed the needs of our growing community of global athletes. Our culture reflects our community. We are continuously striving to hire and engage teammates from all backgrounds, experiences and perspectives because we know we are a stronger team together. Strava is an equal opportunity employer. In keeping with the values of Strava, we make all employment decisions including hiring, evaluation, termination, promotional and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. California Consumer Protection Act Applicant Notice https://docs.google.com/document/d/e/2PACX-1vSc8y6On4NlP5s12hf4kmWe_pvenVyQ78TbtVaz_clROhj9ADQ6kY4YScglBIuY2joKFKalOReX7vP_/pub

Location: Limassol, Cyprus Workplace: on-site Mayflower is a technology company building highload products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience. Now we look for a Data Scientist to join our ML team Job Responsibilities Search & Retrieval Develop and improve retrieval pipelines for large-scale production search systems. Work on candidate generation, query processing, matching, filtering, and retrieval strategies. Improve search relevance, result coverage, and overall SERP quality. Analyse failed searches, irrelevant results, zero-result queries, and other search-quality issues. Explore lexical, semantic, behavioural, hybrid, and vector search approaches. Ranking & Relevance Build, train, and optimise ranking models for search and recommendation systems. Develop learning-to-rank solutions using behavioural, content-based, contextual, and real-time features. Design ranking features based on clicks, conversions, popularity, freshness, availability, and user behaviour. Evaluate ranking quality using Precision, Recall, NDCG, MAP, MRR, and related relevance metrics. Optimise models for low-latency inference and investigate relevance degradation, bias, and feedback loops. Recommendation Systems Develop recommendation models and candidate-generation strategies for personalised and non-personalised scenarios. Build recall and ranking stages for multi-stage recommendation pipelines. Work on related-item, complementary-item, next-action, and behavioural recommendation use cases. Develop user, item, session, and contextual representations. Balance relevance, diversity, novelty, coverage, and business constraints. Experimentation & Evaluation Design and run offline and online experiments for search, ranking, and recommendation improvements. Build evaluation frameworks that connect model quality with product and business outcomes. Design and analyse A/B tests using CTR, conversion, engagement, retention, and revenue-related metrics. Create reproducible pipelines for data preparation, model training, evaluation, and comparison. Evaluate model robustness across traffic segments, query groups, user cohorts, and edge cases. ML Pipelines & Collaboration Build end-to-end ML pipelines for feature generation, training, validation, deployment, and monitoring. Work with high-load, real-time, and low-latency production systems. Process large datasets using Python, SQL, batch pipelines, streaming systems, and Kafka. Collaborate with product, backend, data engineering, and MLOps teams to productionise ML solutions. Communicate technical decisions, experiment results, and trade-offs while contributing to ML best practices. You’ll thrive here if you have Strong hands-on experience building production search, ranking, or recommendation systems. Strong Python and SQL skills for machine learning, data processing, and analytical queries. Practical experience with learning-to-rank, candidate retrieval, search relevance, or recommender-system modelling. Experience building and evaluating multi-stage retrieval and ranking pipelines. Strong understanding of search and recommendation metrics, including Precision, Recall, NDCG, MAP, MRR, CTR, and conversion. Experience with feature engineering and behavioural data such as impressions, clicks, sessions, and conversions. Experience with ML libraries such as scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch, or TensorFlow. Experience working with large-scale production systems, distributed data processing, analytical databases, and streaming platforms. Strong understanding of experimentation and A/B testing, with the ability to independently build, and validate ML solutions. That can be a plus: Experience with Elasticsearch, OpenSearch, Solr, Lucene, or another search-engine stack. Experience with vector databases, approximate nearest neighbour search, and hybrid lexical-semantic retrieval. Experience with query understanding, classification, spell correction, synonyms, or query expansion. Experience with DSSM, two-tower models, BERT-based ranking, cross-encoders, or similar neural architectures. Experience with large-scale data and ML platforms such as Airflow, MLflow Conditions We know that great talent deserves great conditions, so here's what you can expect when joining us: EU-based employment contract and a 3-year Cyprus work visa with full support for your relocation and visa processes, including assistance for your family. Full relocation package: flights to Limassol for you and your family, a company-covered apartment for the first month, and full relocation support to make your move smooth and hassle-free. Transparent performance reviews twice a year, with bonus opportunities and salary adjustments. Private medical insurance for you and your family, a corporate mobile plan (unlimited in Cyprus with roaming included), and interest-free support for car purchases. Provident fund (Cypus): a long-term savings plan co-funded by you and the Company together (available after probation) that grows throughout your time with us in Cyprus. Mindfulness & well-being support, including psychological assistance with 50% coverage. 50% coverage of school and kindergarten fees for your children. Fully covered sports benefits, and also access to in-house electric scooters and bike rentals, and cycling purchase compensation. Investment in your growth: paid language courses and access to suited-for-you development programs, including conferences, training programs, and coaching to support your professional journey. A culture of recognition: a peer reward program to celebrate your contributions. A fully equipped office in Limassol’s city center, with everything you need for deep work and collaboration. Free catering in the office and an in-house coffee bar with high-quality drinks and a health bar stocked with nutritious snacks. A strong engineering culture: international teams, corporate events, team buildings, and hackathons—because great work happens in great communities. Recruitment process HR interview (40 min); Technical interview (1.5 hour); Final interview (45 min).

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We are hiring Machine Learning Engineers across our Consumer Engineering organization, giving you the opportunity to work on a wide range of high-impact problems across the Consumer ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On We are looking for a Staff Machine Learning Engineer to help drive the next generation of Reddit’s ML ecosystem across recommendations, search, messaging, and foundational AI systems. You will lead high-impact initiatives from ideation to production, shaping both technical strategy and product direction across multiple ML domains. This is a highly cross-functional role partnering with Product, Data Science, and Engineering to deliver meaningful user and business impact. This role sits at the intersection of: Relevance & recommendation systems (content, search, notifications) AI-powered discovery & LLM-driven experiences Content and user understanding & large-scale representation learning Large-scale ML infrastructure and pipelines What You’ll Do Lead end-to-end ML initiatives from ideation through production and iteration, shaping technical direction and translating product goals into scalable solutions Architect, build and deploy large-scale ML systems across recommendation, search, and content/user understanding, including retrieval/ranking models, representation learnings embeddings optimizations, and LLM or GenAI-powered capabilities Drive measurable impact on user engagement, discovery, and long-term value Collaborate with cross-functional teams to align product and technical roadmaps and unlock key future ML capabilities Stay at the forefront of AI research, evaluating and introducing new AI/ML paradigms to keep Reddit’s ML ecosystem at the cutting edge Contribute to the development of best practices, guidelines, and ethical AI principles for responsible LLM development and deployment Mentor and guide senior and mid-level ML engineers, fostering a culture of excellence, innovation, and knowledge sharing Set technical vision and drive technical discussions, present findings to leadership, and contribute to long-term ML planning and decision-making Required Qualifications 7+ years of experience building, deploying, and operating machine learning systems in production Deep understanding of machine learning methods, spanning classical approaches and modern deep learning (e.g., Transformers, GNN, etc) Expert at developing and productionizing models using TensorFlow, PyTorch, or Hugging Face Transformers Experience building production-quality code incorporating testing, evaluation, and monitoring using object-oriented programming, including experience in Python and Golang Experience designing and scaling ML systems, including data pipelines, feature engineering, model training/serving, and production monitoring Excellent communication and collaboration skills, with the ability to discuss complex technical topics with diverse teams and translating product needs into scalable ML solutions Track record of driving measurable impact through applied machine learning in real-world products Preferred Qualifications Subject matter expertise in one of the following domains: Recommender systems Search systems (lexical and semantic retrieval and ranking) Content understanding (NLU/NLP/LLM, topic/taxonomy modeling, interest graphs or clustering, and multimodal understanding) Familiarity with distributed systems and large-scale data processing frameworks (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.) Experience working with real-time systems and low-latency production environments Experience with LLM/GenAI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale Strong experimentation rigor, with experience formulating clear hypotheses, designing actionable learning plans and building offline/online correlations Advanced degree in Computer Science, Machine Learning, or related quantitative field Potential Teams Home Experience ML Understanding Feed Relevance Answer Experience Search and Answers Relevance Search Experience Benefits Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave #LI-Remote Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $230,000 — $322,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: San Francisco 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. We are looking for an engineer with strong experience in machine learning and solid foundations in math and computer science to join our growing Post-Training team at Baseten. THE ROLE Custom models are instrumental to the success of Baseten customers. By inference volume, the overwhelming majority of traffic at Baseten is to and from models that have been post-trained in some way, whether that be through reinforcement learning, supervised finetuning, a recent technique from the literature, or an in-house research technique from Baseten. The Post-Training team is responsible for the success of our customers’ post-trained models, and we employ a wide array of techniques to produce models that are more efficient and higher quality than even the biggest closed source models for the customer’s specific needs. Your role as a research engineer is to build the in-house tooling to support all of this. We care about training a wide spectrum of different model architectures with a variety of techniques efficiently and at scale. At times this involves zooming deep into a particular technical topic, but more often it involves working across the stack as a whole - systems-level concepts like Kubernetes, cgroups, storage systems, and networking topologies, as well as PyTorch distributed tensor computation, and GPU kernels. The Manifesto: https://labs.baseten.co/manifesto RECENT RESEARCH - Dense, on-policy or both? https://www.baseten.co/research/dense-on-policy-or-both/ - Repeated kv cache for long-running agents https://www.baseten.co/research/repeated-kv-cache-for-long-running-agents/ - Distillation without the dark – replicating black-box on-policy distillation on Baseten https://www.baseten.co/research/distillation-without-the-dark/ We don’t have a rigid set of skills, but here’s some of what we’re looking for: - A deep understanding of modern ML techniques and tools for training transformers - Advanced experience in a tensor/array computation library like PyTorch, TensorFlow, Jax, or similar - A detailed understanding of transformer training parallelism strategies like data parallelism, sharded data parallelism, tensor parallelism, pipeline parallelism, context parallelism - The experience and knowledge to profile and improve the performance of a distributed GPU program in PyTorch or a similar library - The ability to perform roofline analysis on a transformer training setup - A willingness to dive into messy problems, work with researchers, derive specifications by asking important questions, and execute - Familiarity with HPC and distributed computing platforms like Slurm, Ray, Kubernetes, and Dask - Familiarity with cluster networking technology like Infiniband, RoCE, GPUDirect - Solid fundamentals in operating systems concepts like processes, files, kernel drivers, containerization, and networking protocols - A sense of creativity and willingness to ask difficult questions about our approach, assumptions, and tooling choices 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).

Location: London; New York; Edinburgh; 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 Member of Technical Staff in the Safety for Agents team, you will make a meaningful impact on the development of better, fairer, more trustworthy, and more secure Large Language Models (LLMs). Your primary focus will be on data generation, post-training algorithms, and evaluation methods to ensure Safety in the next generation of models that can access external resources and take actions in the world. You will work closely with other cross-functional machine learning teams and data annotation teams, and will also collaborate with product and policy teams. This role combines expertise in machine learning, ethical and responsible AI, experimental design, and data generation and management. It will require curiosity to tackle totally new scientific problems, engineering skills to implement the pieces we need to test solutions to these, and a desire to dive into messy data and results. You will be on a small team with a lot of autonomy and decision-making power, responsible for making the next generation of LLMs better for society as a whole. Please Note: The existing team work in offices in London, Edinburgh, Paris, Toronto, and New York, but we also embrace being remote-friendly! For this role you need to have ~50% working day overlap with UK/EU timezone (e.g. US East is fine) but there are otherwise no restrictions on where you can be located for this role. Key responsibilities: - Strong statistical skills and experience evaluating scientific experiments related to data collection and model performance. - Extremely strong software engineering skills. - Strong expertise in designing and conducting data collection tasks, including working with human annotators. - Experience analyzing datasets with respect to their quality, biases, and suitability for training ML models. - Hands-on experience training large language models (LLMs) on distributed training infrastructures. - Familiarity with evaluating and improving the generalizability and robustness of ML systems. - Proficiency in programming languages such as Python and ML frameworks (e.g., PyTorch, TensorFlow, JAX). - Excellent communication skills to collaborate effectively with cross-functional teams and present findings. - One or more papers 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: Hong Kong, Hong Kong SAR; Singapore, Singapore Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Team We sit on the front lines of OKX's security and compliance mission. Our charter is to build the flexible, scalable, and intelligent AI systems that detect and prevent identity fraud, account takeover, and large-scale organized abuse — in real time and at the scale of a global financial platform. We own the core identity-risk capabilities that decide, millions of times a day, whether an account can be trusted: identity trust signals, behavioral risk modeling, relationship and cluster intelligence, and face, liveness and document verification. We work shoulder-to-shoulder with Product, Risk, Compliance, and Engineering to turn the hardest adversarial problems in crypto into production-grade defenses that protect good users and the open financial system. About the Role We are looking for a Senior AI Engineer to design, build, and own key identity-risk and trust models at OKX. You will build models that combine identity verification results, device and geo data, and user behavior into trust and risk signals, and use graph and clustering methods to uncover organized, industrialized fraud. This is an end-to-end, research-to-production role: you will own algorithms in your domain and ship models into real-money, high-risk, large-scale production environments. You will be a hands-on technical contributor who works closely with Product, Risk, and Compliance, and who helps raise the technical bar of the team. Your domains span: Identity trust & risk modeling — fusing verification scores, device, geo, and behavioral data into identity-quality and trust signals. Cluster & relationship intelligence — graph and clustering methods to identify account farms, mass registration, and coordinated attacks. Behavioral risk modeling — behavioral features and sequence models for account takeover and abnormal-session detection. Biometric & multimodal signals — face embeddings, liveness/anti-spoofing, DeepFake and injection defense, document forgery and AIGC detection, used as inputs to identity trust and the risk layer. AI agents — applying agentic AI to scale investigation, detection, and operational defense. What You'll Be Doing Build identity trust & risk models: Design and ship coarse-to-fine risk models that fuse face/liveness/document verification scores, device, IP and geo signals, and behavioral data, for high-concurrency real-time decisioning. Uncover organized fraud with graph & clustering: Build entity graphs across accounts, devices, faces, documents and templates, and apply community detection, clustering, and GNN methods to detect fraud rings and large-scale abuse. Develop behavioral features & sequence models: Engineer real-time and offline behavioral features, and build sequence models to detect account takeover, bot/script behavior, and abnormal sessions. Leverage biometric & multimodal signals: Turn biometric features (face embeddings, face quality, liveness and anti-spoofing results) and document-forgery and DeepFake signals into reliable identity-trust inputs for risk decisions, including biometric similarity for cross-account linkage and duplicate-identity detection. Work with the face, liveness, and document teams, or build models yourself. Drive execution & collaboration: Deliver measurable results while managing ambiguity; partner with backend, product, infrastructure, risk, and compliance teams to integrate models into the production decision chain. Own metric definitions, the balance between false positives and missed fraud, pass rate, monitoring, and drift handling. Advance applied R&D: Experiment with graph learning, multimodal fusion, and AI agents; stay current with academic and industry advances and translate them into practical defenses. Raise the technical bar: Contribute to design reviews, share applied-AI best practices, and mentor junior engineers. What We Look For 5+ years of hands-on experience building risk-control, fraud-detection, or identity-trust models, including significant experience deploying ML systems into production. Graph & clustering expertise: Experience applying graph mining, community detection, clustering, or GNN methods to fraud or abuse detection. Behavioral modeling: Solid experience with behavioral feature engineering and sequence modeling, including real-time feature pipelines. Deep AI/ML expertise: Strong proficiency with PyTorch and/or TensorFlow, and solid experience with production ML systems. Strong technical & coding skills: Strong coding ability (e.g., Python, SQL) and the system-level thinking to design end-to-end solutions with high availability and low latency. Adversarial mindset: Understanding of how fraudsters adapt, and how to evaluate and iterate defenses against evolving attacks. Collaboration: Strong communication skills, with experience working across engineering, product, and risk teams. Education: Bachelor's degree or higher in Computer Science, Electrical Engineering, or a related field. Preferred Qualifications Experience in identity verification, KYC/KYB, AML, face-payment or payment risk control, or biometric security. Hands-on experience with face recognition, liveness/anti-spoofing, OCR, document parsing, fake-ID detection, or media forensics. Experience with graph databases or graph computing (e.g., Neo4j, GraphX) and real-time graph features. Knowledge of data and AI/ML infrastructure (e.g., Spark, Flink, Kafka, Airflow, Snowflake). Familiarity with MLOps best practices: monitoring, retraining, and continuous improvement of production models. Experience with LLMs and AI agents. Experience working in fast-paced technology companies or security-critical environments. Research publications, patents, or open-source contributions in relevant AI fields. Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Staff ML Infrastructure Engineer, you will lead development of a platform for large scale ML models at Reddit. Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges Who You Might Be: 8+ years of experience in ML infrastructure, including model training and model deployments Hands-on experience with ML optimization, including memory and GPU profiling Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb) Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc. Deep experience working with distributed training frameworks, including Ray and Kubernetes Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle. Strong organizational & communication skills Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus Experience working with graph neural networks (GNNs) and associated graph ML frameworks (PyTorch Geometric, Deep Graph Library) is a big plus Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $230,000 — $322,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior ML Infrastructure Engineer, you will lead development of a platform for large scale ML models at Reddit. Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges Who You Might Be: 5+ years of experience in ML infrastructure, including model training and model deployments Hands-on experience with ML optimization, including memory and GPU profiling Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb) Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc. Deep experience working with distributed training frameworks, including Ray and Kubernetes Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle. Strong organizational & communication skills Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus Experience working with graph neural networks (GNNs) and associated graph ML frameworks (PyTorch Geometric, Deep Graph Library) is a big plus Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $216,700 — $303,400 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

О ПРОЕКТЕ DigiNavi — это иммерсивная AR-навигация для крупных общественных пространств (ТЦ, аэропорты). Мы превращаем локации в SMART-зоны с помощью Computer Vision и дополненной реальности. Наша команда внедряет подход VibeCoding: вы выступаете архитектором решений, используя AI-агентов (Claude Code, Cursor) как основной инструмент исполнения. ЧЕМ ПРЕДСТОИТ ЗАНИМАТЬСЯ — AI-Driven Development: Разработка и поддержка кода через AI-инструментарий. — R&D & Prototyping: Быстрая проверка гипотез и внедрение алгоритмов (SuperPoint, NetVLAD, Gaussian Splatting). — Architecture: Рефакторинг CV-компонентов в гетерогенной среде (Go / C++ / Python). — Integration: Внедрение ML-моделей в микросервисную архитектуру через gRPC и Kafka. — Optimization: Работа с high-load системами и оптимизация инференса моделей. ЧТО МЫ ЖДЕМ ОТ ВАС — CV & ML Expert: Глубокие знания PyTorch и OpenCV. Опыт создания Computer Vision решений. — VibeCoding Skills: Практический опыт работы с Claude Code, Cursor или аналогами. Понимание SDD и TDD подходов. — Backend: Опыт production-развертывания (FastAPI, Docker) и понимание микросервисов. — Polyglot Mindset: Готовность работать в окружении, где используются Go и C++ (чтение и интеграция). — Документация: Умение создавать техническую документацию и структурировать процессы там, где их нет. БУДЕТ ПЛЮСОМ — Опыт оптимизации инференса для мобильных платформ. — Работа с облачной инфраструктурой GCP. — Понимание специфики разработки в сфере AR/VR.

Location: Remote, Canada Workplace: remote At PointClickCare our mission is simple: to help providers deliver exceptional care. And that starts with our people. As a leading health tech company that’s founder-led and privately held, we empower our employees to push boundaries, innovate, and shape the future of healthcare.   With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in millions of lives. We also reinvest a significant percentage of our revenue back into research and development, ensuring our employees have the resources to innovate and make a lasting impact. Recognized by Forbes as a top private cloud company and honored as one of Canada’s Most Admired Corporate Cultures, we offer flexibility, growth opportunities, and meaningful work.    At PointClickCare, we empower our people to be the architects of a smarter healthcare future; one that is human-first and accelerated by AI to create meaningful and lasting change. Employees harness AI as a catalyst for creativity, productivity, and thoughtful decision-making. By integrating AI tools into our daily workflows, collaboration is enhanced, outcomes are improved, and every team member has the proficiency to maximize their impact. It all starts with our hiring practices where we uncover AI expertise that complements our mission, and we continue to invest in training and development to nurture innovation throughout the employee journey.   Join us in redefining healthcare — so it doesn’t just survive, it thrives. To learn more about PointClickCare, check out Life at PointClickCare and connect with us on Glassdoor and LinkedIn.     **Travel to Office expectations** For Remote Roles: If this role is remote, there will be in-office events that will require travel to and from the Mississauga and/or Salt Lake City office. These will include, but not limited to, onboarding, team events, semi-annual and annual team meetings.   For Hybrid Roles: If this role is Hybrid, there will be an expectation to reside within commutable distance to the office/location specified in the job listing. This will include, but not limited to, weekly/bi-weekly/monthly events in the office with your specific team. This is a requirement for this role. The Role   We're looking for an applied AI researcher who has worked hands-on with healthcare data and is building modern LLM, RAG, and agentic AI systems.   Reporting to the Vice President, Advanced Technology, you will be a member of the Advanced Technology / Applied AI Research team at PointClickCare.   You are a talented Senior Applied Researcher, looking to make a difference solving critical customer and business challenges in the dynamic healthcare market. You thrive applying creative and pragmatic solutions—from framing problems and preparing data, to selecting appropriate techniques, building and evaluating model systems—that will truly transform healthcare and enable our customers to deliver exceptional care.   Responsibilities - Apply machine learning and AI techniques including GenAI and LLM-based approaches to develop model systems and solutions, collaborating across functions to scale and integrate these into large-scale cloud-based SaaS production environments for healthcare. - Work with product leaders, clinical informaticists, data scientists, UI/UX researchers, engineers, and healthcare professionals to design and deliver high value solutions. - Design, build and evaluate solutions that may involve structured or unstructured data for healthcare use cases, delivering capabilities such as predictive models, summarization, recommenders, semantic search, extraction, classification, or other AI/ML applications - Perform research and experimentation to select appropriate approaches, algorithms, and evaluation methods, and execute the R&D needed to deliver production-ready model systems. - Perform data collection, cleaning, analysis, prompt tuning, parameter fine-tuning, model training, development, and evaluation—using existing or developing new tools or workflows as needed. - Apply and help evolve responsible AI evaluation practices, using approaches and frameworks such as LLM-as-judge, RAGAS, and LangSmith, and design and implement custom model performance and quality metrics as needed to ensure model quality, fairness, and safety at scale. - Contribute to a collaborative team culture, sharing knowledge and helping develop new capabilities across the organization.   Required Experience - Ph.D grad, with 1+ years related industry experience OR Masters grad with 4+ years industry experience--including at least 1 year directly related to healthcare ML/AI       - Proven industry experience through multiple major product releases in a commercial SaaS environment. - Hands-on experience working with healthcare data (e.g. EHR, ADT, clinical notes). - Proficiency in Python. Proficiency in Java or other languages helpful. - Proficiency with SQL and data engineering for AI/ML applications. - Experience working with large datasets using big data frameworks (e.g. Azure Data Lake, Apache Spark or Databricks) - Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers. - Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM. - Experience building and deploying models using public cloud infrastructure (Azure, AWS, or Google Cloud), including familiarity with version control, CI/CD pipelines, and scaling considerations for production ML systems at SaaS scale. - Strong communication and collaboration skills; comfortable working on a distributed team. - Experience with one or more of: reinforcement learning or RLHF, NLP techniques for summarization, extraction, classification, or semantic search, retrieval-augmented generation (RAG) pipelines and/or agentic frameworks (e.g. LangChain, LlamaIndex).    #LI-AV1 #LI-remote PointClickCare Benefits & Perks:   Benefits starting from Day 1! Retirement Plan Matching Flexible Paid Time Off Wellness Support Programs and Resources Parental & Caregiver Leaves Fertility & Adoption Support Continuous Development Support Program Employee Assistance Program Allyship and Inclusion Communities Employee Recognition … and more!   It is the policy of PointClickCare to ensure equal employment opportunity without discrimination or harassment on the basis of race, religion, national origin, status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, veteran status, genetic information, or any other basis protected by law. PointClickCare welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process. Please contact recruitment@pointclickcare.com should you require any accommodations. As part of our commitment to a streamlined and equitable hiring experience, PointClickCare uses AI tools to assist with candidate screening and assessment.   When you apply for a position, your information is processed and stored with Lever, in accordance with Lever’s Privacy Policy. We use this information to evaluate your candidacy for the posted position. We also store this information, and may use it in relation to future positions to which you apply, or which we believe may be relevant to you given your background. When we have no ongoing legitimate business need to process your information, we will either delete or anonymize it.  If you have any questions about how PointClickCare uses or processes your information, or if you would like to ask to access, correct, or delete your information, please contact PointClickCare’s human resources team: recruitment@pointclickcare.com    PointClickCare is committed to Information Security. By applying to this position, if hired, you commit to following our information security policies and procedures and making every effort to secure confidential and/or sensitive information. At PointClickCare, base salary is one of the many components that make up our total rewards package. The CAD base salary range for this position is $144,000-181,000 (not overtime eligible) + bonus + benefits. Compensation is assessed individually and aligned to experience, skills, and market context. The posted range reflects typical expectations for this role.

Location: Remote - US Workplace: remote At PointClickCare our mission is simple: to help providers deliver exceptional care. And that starts with our people. As a leading health tech company that’s founder-led and privately held, we empower our employees to push boundaries, innovate, and shape the future of healthcare.   With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in millions of lives. We also reinvest a significant percentage of our revenue back into research and development, ensuring our employees have the resources to innovate and make a lasting impact. Recognized by Forbes as a top private cloud company and honored as one of Canada’s Most Admired Corporate Cultures, we offer flexibility, growth opportunities, and meaningful work.    At PointClickCare, we empower our people to be the architects of a smarter healthcare future; one that is human-first and accelerated by AI to create meaningful and lasting change. Employees harness AI as a catalyst for creativity, productivity, and thoughtful decision-making. By integrating AI tools into our daily workflows, collaboration is enhanced, outcomes are improved, and every team member has the proficiency to maximize their impact. It all starts with our hiring practices where we uncover AI expertise that complements our mission, and we continue to invest in training and development to nurture innovation throughout the employee journey.   Join us in redefining healthcare — so it doesn’t just survive, it thrives. To learn more about PointClickCare, check out Life at PointClickCare and connect with us on Glassdoor and LinkedIn.     **Travel to Office expectations** For Remote Roles: If this role is remote, there will be in-office events that will require travel to and from the Mississauga and/or Salt Lake City office. These will include, but not limited to, onboarding, team events, semi-annual and annual team meetings.   For Hybrid Roles: If this role is Hybrid, there will be an expectation to reside within commutable distance to the office/location specified in the job listing. This will include, but not limited to, weekly/bi-weekly/monthly events in the office with your specific team. This is a requirement for this role. The Role   We're looking for an applied AI researcher who has worked hands-on with healthcare data and is building modern LLM, RAG, and agentic AI systems.   Reporting to the Vice President, Advanced Technology, you will be a member of the Advanced Technology / Applied AI Research team at PointClickCare.   You are a talented Senior Applied Researcher looking to make a difference solving critical customer and business challenges in the dynamic healthcare market. You thrive applying creative and pragmatic solutions—from framing problems and preparing data, to selecting appropriate techniques, building and evaluating model systems—that will truly transform healthcare and enable our customers to deliver exceptional care.   Responsibilities - Apply machine learning and AI techniques including GenAI and LLM-based approaches to develop model systems and solutions, collaborating across functions to scale and integrate these into large-scale cloud-based SaaS production environments for healthcare. - Work with product leaders, clinical informaticists, data scientists, UI/UX researchers, engineers, and healthcare professionals to design and deliver high value solutions. - Design, build and evaluate solutions that may involve structured or unstructured data for healthcare use cases, delivering capabilities such as predictive models, summarization, recommenders, semantic search, extraction, classification, or other AI/ML applications - Perform research and experimentation to select appropriate approaches, algorithms, and evaluation methods, and execute the R&D needed to deliver production-ready model systems. - Perform data collection, cleaning, analysis, prompt tuning, parameter fine-tuning, model training, development, and evaluation—using existing or developing new tools or workflows as needed. - Apply and help evolve responsible AI evaluation practices, using approaches and frameworks such as LLM-as-judge, RAGAS, and LangSmith, and design and implement custom model performance and quality metrics as needed to ensure model quality, fairness, and safety at scale. - Contribute to a collaborative team culture, sharing knowledge and helping develop new capabilities across the organization.   Required Experience - Ph.D. grad, with 1+ years related industry experience OR Masters grad with 4+ years industry experience--including at least 1 year directly related to healthcare ML/AI       - Proven industry experience through multiple major product releases in a commercial SaaS environment. - Hands-on experience working with healthcare data (e.g. EHR, ADT, clinical notes). - Proficiency in Python. Proficiency in Java or other languages helpful. - Proficiency with SQL and data engineering for AI/ML applications. - Experience working with large datasets using big data frameworks (e.g. Azure Data Lake, Apache Spark or Databricks) - Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers. - Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM. - Experience building and deploying models using public cloud infrastructure (Azure, AWS, or Google Cloud), including familiarity with version control, CI/CD pipelines, and scaling considerations for production ML systems at SaaS scale. - Strong communication and collaboration skills; comfortable working on a distributed team. - Experience with one or more of: reinforcement learning or RLHF, NLP techniques for summarization, extraction, classification, or semantic search, retrieval-augmented generation (RAG) pipelines and/or agentic frameworks (e.g. LangChain, LlamaIndex).    #-LI-AV1 #LI- remote PointClickCare Benefits & Perks:   Benefits starting from Day 1! Retirement Plan Matching Flexible Paid Time Off Wellness Support Programs and Resources Parental & Caregiver Leaves Fertility & Adoption Support Continuous Development Support Program Employee Assistance Program Allyship and Inclusion Communities Employee Recognition … and more!   It is the policy of PointClickCare to ensure equal employment opportunity without discrimination or harassment on the basis of race, religion, national origin, status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, veteran status, genetic information, or any other basis protected by law. PointClickCare welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process. Please contact recruitment@pointclickcare.com should you require any accommodations. As part of our commitment to a streamlined and equitable hiring experience, PointClickCare uses AI tools to assist with candidate screening and assessment.   When you apply for a position, your information is processed and stored with Lever, in accordance with Lever’s Privacy Policy. We use this information to evaluate your candidacy for the posted position. We also store this information, and may use it in relation to future positions to which you apply, or which we believe may be relevant to you given your background. When we have no ongoing legitimate business need to process your information, we will either delete or anonymize it.  If you have any questions about how PointClickCare uses or processes your information, or if you would like to ask to access, correct, or delete your information, please contact PointClickCare’s human resources team: recruitment@pointclickcare.com    PointClickCare is committed to Information Security. By applying to this position, if hired, you commit to following our information security policies and procedures and making every effort to secure confidential and/or sensitive information. At PointClickCare, base salary is one of the many components that make up our total rewards package. The USD base salary range for this position is $163,000-204,000 (not overtime eligible) + bonus + benefits. Compensation is assessed individually and aligned to experience, skills, and market context. The posted range reflects typical expectations for this role.

Задачи: — Разработка и поддержка кода с использованием AI-агентов (Claude Code, Cursor, OpenAI Codex и др.). — Рефакторинг AI/ML и CV-компонентов в условиях гетерогенной среды (Go / C++ / Python). — Быстрое прототипирование гипотез и внедрение новых алгоритмов. — Интеграция ML-моделей в микросервисную архитектуру (gRPC / Kafka). — Оптимизация инференса и работа с high-load системами. Требования: — Уверенный уровень Python, опыт разработки AI/Computer Vision решений. — Знание алгоритмов (SuperPoint, NetVLAD, Gaussian Splatting), опыт работы с PyTorch, OpenCV. — Практический опыт работы с AI Tools: Claude Code, Cursor, Antigravity или аналогами, понимание workflow VibeCoding. — Опыт production-развёртывания ML-сервисов (FastAPI, Docker, gRPC), понимание микросервисной архитектуры (Kafka). — Готовность работать в окружении с Go и C++ (чтение, интеграция, базовое понимание). — Понимание и применение SDD (Specification-Driven) и TDD подходов. — Умение быстро прототипировать и проверять гипотезы. — Опыт работы с технической документацией и умение создавать её. Преимущества: — Опыт оптимизации inference для мобильных и серверных сред. — Опыт работы с облачной инфраструктурой GCP. — Понимание специфики AR/VR разработки. Условия: — Режим оформления: ТК/ИП — Удаленная работа — Гражданство РФ

Location: Intellias Meet your recruiter Gerasim Naydenov gerasim.naydenov@intellias.com https://www.linkedin.com... Vacancy details Software Engineering Python Engineer Senior Bulgaria, Croatia Hybrid APPLY NOW REFER A FRIEND Let’s breathe life into great tech ideas! With more than 3 000 people globally, Intellias is a company where benchmark technological solutions are born. Join in and take your part in digitalizing the world. What project we have for you Our team operates at the frontlines of our efforts to support Google and owns the campaign management functionalities that allow users to scale, automate and optimize their ad operations on Google Ads. Join us in building new end-to-end automation solutions and scaling existing automation pipelines to help our customers automatically launch and iterate their Google advertising. The team has recently started working with exciting new campaign types within Google Ads and we’re looking to scale up our team to expand our Google Ads offering. What you will do Design, build and maintain backend services that sit at the core of client campaign optimization products. Be a core contributor of our team and our ways of working to build high impact products. You’ll actively be involved in work planning, retrospectives, and overall team improvement. Support data scientists in bringing machine learning models to production. Mentor your team on software development practices and propagate best practices like testing, monitoring, or clean code. Use your skills and experience to continuously improve our software architecture, coding practices, tools, and processes. Work with our stakeholders – be them product, engineering, infrastructure – to ensure we meet customers where they are. Being able to translate business/product needs to viable solutions is a must. Apply and enhance your soft skills through working closely with your colleagues and our customers. Doing knowledge shares, running productive meetings, and pair programming/debugging are just some ways we grow our soft skills. Impact the daily life of the staff of the hundreds of advertisers using client platform What you need for this We’re seeking an experienced Software Engineer with Strong Python skills Strong experience in Data Science, NLP, Generative AI demonstrated through relevant projects or research. Proficiency in programming languages such as Python and libraries/frameworks like FastAPI, pandas, polars, TensorFlow, PyTorch, etc. and cloud AI services Aws/Azure/GCP Proven ability to bridge the gap between technical concepts and business impact, with a clear understanding of how data science aligns with business goals. Excellent communication skills, strong sense of ownership and ability challenge product decisions with both technical and non-technical stakeholders. Experience developing and maintaining services under SLA Analytical mindset with a problem-solving approach Passion for solving customer challenges quickly while making thoughtful architectural decisions Adaptability and resilience when facing new or ambiguous challenges Strong written and verbal communication skills in English M.Sc. in a relevant field is preferred Nice to have: Experience with CausalML frameworks. Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills AI/ML AWS GCP Python

Location: London, England, United Kingdom About Wheely Wheely is redefining premium transportation across major cities in Europe, the US, and the Middle East. We blend cutting-edge technology with the craft of five-star chauffeuring to deliver an experience trusted by more than 100,000 active riders and 1,200 corporate accounts. We’re a profitable, fast-growing scale-up with $43M raised and over $100M in annual revenue. Having recently launched in New York City, we’re expanding rapidly across the US and EMEA. If you take pride in your craft and want to help shape the next chapter of our growth, we'd love to hear from you. About The Role We're hiring Associate Data Scientists with a background in Operations Research. You will own the entire process: from ideation and research through to production deployment. You'll join either our Pricing or Matching team, working alongside other Data Scientists and engineers on challenging, high-impact problems such as dynamic pricing and bipartite matching. Responsibilities Collaborate with engineers, Data Scientists, designers, and product managers to solve ambiguous problems Research, prototype, and ship ML and optimisation models into production Continuously improve existing algorithms and identify opportunities for new ones Requirements Master's or PhD in Operations Research, Mathematics, Management Science or a closely related field with a focus on optimisation Strong foundation in mathematical optimisation or mathematical programming Solid knowledge of probability & statistics Solid knowledge of Reinforcement Learning and Casual Inference Excellent programming skills in Python and core ML tooling (e.g. SQL, PyTorch, etc.) Nice To Have Exposure to dynamic pricing, auction design, or marketplace matching problems Publication in Q1/A* journals, participation in NeurIPS and other conferences What We Offer Office-based role in West London, four days a week with flexible start and finish times, plus one remote day of your choice Salary: £50,000 – £70,000 Employee stock options plan Private medical and dental insurance Life and critical illness cover Latest-generation MacBook Pro and 4k display Monthly credit towards Wheely journeys Cycle to Work scheme Professional development stipend All of your personal information will be collected stored and processed in accordance with Wheely’s Candidate Privacy Notice

Location: Λευκωσία, Nicosia, Cyprus About Wheely Wheely is redefining premium transportation across major cities in Europe, the US, and the Middle East. We blend cutting-edge technology with the craft of five-star chauffeuring to deliver an experience trusted by more than 100,000 active riders and 1,200 corporate accounts. We’re a profitable, fast-growing scale-up with $43M raised and over $100M in annual revenue. Having recently launched in New York City, we’re expanding rapidly across the US and EMEA. If you take pride in your craft and want to help shape the next chapter of our growth, we'd love to hear from you. About The Role We're hiring Associate Data Scientists with a background in Operations Research. You will own the entire process: from ideation and research through to production deployment. You'll join either our Pricing or Matching team, working alongside other Data Scientists and engineers on challenging, high-impact problems such as dynamic pricing and bipartite matching. Responsibilities Collaborate with engineers, Data Scientists, designers, and product managers to solve ambiguous problems Research, prototype, and ship ML and optimisation models into production Continuously improve existing algorithms and identify opportunities for new ones Requirements Master's or PhD in Operations Research, Mathematics, Management Science or a closely related field with a focus on optimisation Strong foundation in mathematical optimisation or mathematical programming Solid knowledge of probability & statistics Solid knowledge of Reinforcement Learning and Casual Inference Excellent programming skills in Python and core ML tooling (e.g. SQL, PyTorch, etc.) Nice To Have Exposure to dynamic pricing, auction design, or marketplace matching problems Publication in Q1/A* journals, participation in NeurIPS and other conferences What We Offer Office-based role in Nicosia, four days a week with flexible start and finish times, plus one remote day of your choice Competitive salary Employee stock options plan Private medical and dental insurance Daily Lunch allowance Latest-generation MacBook Pro and 4k display Professional development stipend Relocation support, including visa sponsorship and allowance All of your personal information will be collected stored and processed in accordance with Wheely’s Candidate Privacy Notice

Location: Palo Alto; Montréal Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. Role Summary    -You will be working with the research team on making state-of-the-art generative models. -You will run autonomous work streams under the supervision of experienced scientists. -The role is based in our Palo Alto or Montreal office. -Internship duration : 3-6 months. We will only consider candidates looking for end of studies internships (Master or Phd)   What you will do   -Explore state-of-the-art LLM algorithms for training LLMs, with the supervision of top level scientists. -Assist in the design and implementation of machine learning models and algorithms. -Conduct research on the latest advancements in natural language processing and LLMs. -Contribute to the development and optimization of our LLM systems. -Collaborate with cross-functional teams to integrate LLM technologies into various applications. -Perform data analysis and visualization to support research and development efforts. -Document research findings and contribute to technical reports and publications. -Participate in team meetings and brainstorming sessions to share ideas and insights   About you   -Currently doing a Master or PhD at a tier 1 engineering schools / Universities. -High scientific understanding of the field of generative AI.  -Broad knowledge of the field of AI, and specific knowledge or interest in fine-tuning and using language models for applications. -Strong programming skills in Python, with experience in libraries such as TensorFlow, PyTorch, or similar. -Familiarity with natural language processing techniques and machine learning algorithms. -Design complex software and make them usable in production.  -Navigate the full MLOps technical stack, with a focus on architecture development and model evaluation and usage.  -Previous experience with LLMs or related technologies. -Knowledge of deep learning frameworks and techniques..Experience with version control systems (e.g., Git) and linux shell environment.   Now, it would be ideal if you :  -Have experience in fine tuning LLMs. -Have used complex HPC infrastructure with full autonomy.   WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

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. 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 Research Engineer to join our Pretraining 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. Key Responsibilities: Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development Independently lead small research projects while collaborating with team members on larger initiatives Design, run, and analyze scientific experiments to advance our understanding of large language models Optimize and scale our training infrastructure to improve efficiency and reliability Develop and improve dev tooling to enhance team productivity Contribute to the entire stack, from low-level optimizations to high-level model design Qualifications: Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field Strong software engineering skills with a proven track record of building complex systems Expertise in Python and experience with deep learning frameworks (PyTorch preferred) Familiarity with large-scale machine learning, particularly in the context of language models Ability to balance research goals with practical engineering constraints Strong problem-solving skills and a results-oriented mindset Excellent communication skills and ability to work in a collaborative environment Care about the societal impacts of your work Preferred Experience: Work on high-performance, large-scale ML systems Familiarity with GPUs, Kubernetes, and OS internals Experience with language modeling using transformer architectures Knowledge of reinforcement learning techniques Background in large-scale ETL processes You'll thrive in this role if you: Have significant software engineering experience Are results-oriented with a bias towards flexibility and impact Willingly take on tasks outside your job description to support the team Enjoy pair programming and collaborative work Are eager to learn more about machine learning research Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research projects Are working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research View research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximize the impact of your insights Have ambitious goals for AI safety and general progress in the next few years, and you’re working to create the best outcomes over the long-term. Sample Projects: Optimizing the throughput of novel attention mechanisms Comparing compute efficiency of different Transformer variants Preparing large-scale datasets for efficient model consumption Scaling distributed training jobs to thousands of GPUs Designing fault tolerance strategies for our training infrastructure Creating interactive visualizations of model internals, such as attention patterns At Anthropic, we are committed to fostering a diverse and inclusive workplace. We strongly encourage applications from candidates of all backgrounds, including those from underrepresented groups in tech. If you're excited about pushing the boundaries of AI while prioritizing safety and ethics, we want to hear from you! 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 — £630,000 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.