Top Machine Learning Engineer Jobs Openings in 2025

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About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.About the role: Anthropic’s performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training.  As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems.  You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment.   Responsibilities: Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems Become familiar with the team’s technical stack enough to make targeted contributions as an individual contributor Manage day-to-day execution of the team's work Prioritize the team’s work and manage projects in a highly dynamic, fast paced environment Coach and support your reports in understanding, and pursuing, their professional growth Maintain a deep understanding of the team's technical work and its implications for AI safety   You may be a good fit if you: Have 1+ years of management experience in a technical environment, particularly performance or distributed systems Have a background in machine learning, AI, or a similar related technical field Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development Excel at building strong relationships with stakeholders at all levels Are a quick learner, capable of understanding and contributing to discussions on complex technical topics Have experience managing teams through periods of rapid growth and change Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level of abstraction) to be effective   Strong candidates may also have experience with:  High performance, large-scale ML systems GPU/Accelerator programming ML framework internals OS internals Language modeling with transformers The expected salary range for this position is:Annual Salary:$425,000—$560,000 USDLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. 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.

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Somite.ai is a venture-backed company transforming stem cell biology with AI.  We recently raised over $47 million in a Series A funding round, bringing our total funding to about $60 million.  Just as LLMs revolutionized human language, we’re decoding the language of cells—how they communicate and decide their fate—using vast amounts of in-house generated data. Our AI models enable precise control over cell behavior, unlocking the potential to engineer therapies for diseases like diabetes, neurodegenerative diseases, and muscular dystrophies. Our platform, DeltaStem, accelerates therapy creation and continually improves through data-driven insights.Founded by Dr. Micha Breakstone, a serial AI entrepreneur from MIT, and three Harvard Medical School professors, including the Chair of Genetics, Somite.ai is at the forefront of a new era in healthcare.Location: BostonClick the following links to learn more about Somite:https://x.com/SomiteAi/status/1922284999891472808https://www.forbes.com/sites/gilpress/2025/05/13/somite-ai-raises-47m-series-a-to-reinvent-cell-replacement-therapy/Click the following link to Apply: https://jobs.ashbyhq.com/somite-ai?utm_source=0pRNP5YXRZAbout the Role:As a Machine Learning Engineer - Biological Foundational Models, you will play a key role in developing foundational models for single-cell RNA sequencing data. Working closely with other machine learning researchers and computational biologists, you’ll design cutting-edge AI solutions, contribute to pioneering research, and help build the core infrastructure driving Somite’s cell-replacement therapy platform. This role is ideal for someone passionate about applying machine learning to solve complex biological challenges.Responsibilities:●       Drive the development of machine learning models for biological data, from research and prototyping to production deployment●       Design, train, and optimize foundational models for single-cell RNA sequencing and other high-dimensional omics data●       Build scalable, distributed pipelines for training and inference across trillion-token biological datasets●       Collaborate closely with computational biologists to ensure models produce biologically meaningful, interpretable outputs, engaging deeply with biological questions and research●       Design and implement novel deep learning architectures, including transformer-based models tailored to biological dataQualifications:●       7+ years of experience in machine learning, deep learning, and large-scale data analysis, preferably in biological applications.●       Master’s degree or higher in Computer Science, Artificial Intelligence, Computational Biology, or a related field.●       Strong proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.●       Proven experience building and optimizing large-scale models, including transformer-based architectures.●       Demonstrated track record of independent research and end-to-end model development, from prototyping to production.●       Passion for AI-driven biology and its potential to transform healthcare.Preferred Qualifications:●       Strongly preferred: extensive background in biological research and biological modeling, ideally with single-cell RNA sequencing data●       Strongly preferred: 3+ years of professional software engineering experience in an industry setting.●       Experience with reinforcement learning techniques such as RLHF, PPO.●       Experience in startups or fast-paced environments, with a self-directed, proactive work style.Click the following link to Apply: https://jobs.ashbyhq.com/somite-ai?utm_source=0pRNP5YXRZBenefits:●       Take a technical leadership role with a mission-driven company with the potential to significantly impact the lives of millions.●       Work alongside a talented and passionate team at the forefront of AI and cellular biology.●       Contribute to the development of groundbreaking therapies that address significant unmet medical needs.●       Enjoy a competitive salary and benefits package, including flexible work options.Exceptional candidates who demonstrate outstanding capabilities and potential will be considered, even if they do not meet every qualification listed.Join us and help unlock the full potential of AI for the benefit of human health!

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About Norm AiNorm Ai is the Compliance AI Platform for legal standards-based reasoning & workflow automation. We developed the first Domain Specific Language (DSL) for fully representing regulatory requirements in AI code. This DSL, deployed with our enterprise platform, enables Norm clients to transform workflows and apply compliance checks at the source of business activities.By building and deploying Government-Grade Regulatory AI, we are setting the norms for compliance processes at the largest institutions in the world, and laying the groundwork for the deployment of AI agents more broadly in highly regulated workflows. Our client base includes firms with a combined $17 Trillion in AUM, and growing quickly. Our Software Engineers came from Palantir, Google, Meta, AWS, Harvard, Stanford, and MIT. Our Legal Engineers are from Harvard Law, Stanford Law, Yale Law, Sullivan & Cromwell, Simpson Thacher, Davis Polk, Greenberg Traurig, the SEC, and FINRA.We have raised capital over the past 18 months from Vanguard, Blackstone, Bain Capital, Coatue, Craft Ventures, New York Life, Citi, TIAA, Larry Summers, and Marc Benioff.This RoleAs an Applied AI Research Engineer at Norm Ai, you will take a methodical and holistic approach to increasing the coverage and capabilities of our automation platform. You will collaborate closely with and act as a bridge between our software engineering, legal engineering, and product teams to design and refine our AI-driven compliance solutions.You Will:Design and build AI-powered, enterprise-grade software to meet rapidly increasing demands.Regularly contribute performant and high-quality code to our production codebase that conforms to the high standards of our software engineering team. Autonomously prioritize between development velocity and long-term robustness of proposed solutions, always with a ruthless propensity for action.Run experiments with new LLM techniques and technologies across our AI infrastructure, content processing, and regulatory workflows.Write prompts, iterate on them, and design systems for continuous improvement.Develop regulatory expertise that can be used as part of our LLM workflows.Skills & Experience - Core4+ years of experience as a Software Engineer, ML engineer, or Data Scientist.Strong programming skills in Python, proficiency in Docker and data storage technologies such as Postgres and Redis.Willingness to work with frontend technologies (Typescript, react, etc) when required.Experience in AI/ML infrastructure and tooling.Interest in becoming a regulatory domain expert and working closely with legal and regulatory professionals.Strong reading and writing skills.Strong quantitative skills that can enable a data-driven approach to problem solving.Skills & Experience - PlusesExperience deriving insights from PDFs and/or other unstructured or semi-structured data typesFamiliarity with the latest research in LLMs and an eagerness to adopt new model capabilities as they become availableBackground working on complex compliance or regulatory systems.What Success Looks Like - 30 DaysNorm Ai Integration: Rapidly familiarize yourself with Norm Ai's existing codebase, architecture, and the unique challenges of our AI-driven compliance solutions. Within the first two weeks, we expect meaningful contributions to our production codebases.AI Engineering: Rapidly familiarize yourself with the data flows in Norm Ai’s compliance systems and enhance the accuracy or robustness of one of our core modules.Domain Expertise: Develop familiarity with the underlying regulations with which Norm works.What Success Looks Like - 60 DaysNorm Ai Integration: Successfully optimize, implement, and deploy significant features that improve the accuracy and coverage of our automation platform.AI Engineering: Effectively lead large-scale improvements to our AI system, including runtime optimizations and accuracy improvements.Domain Expertise: Leverage regulatory expertise to effectively collaborate with the legal engineers and improve new and existing LLM workflows$200,000 - $250,000 a yearThe range displayed in this job posting reflects the minimum and maximum target for new hire salary for this position. Within the range, individual pay is determined by various factors, including job-related skills (as uncovered during the interview process), experience, and relevant education or training. Please note that the compensation details listed here reflect the base salary only, and do not include equity or benefits. We offer a competitive salary along with equity compensation. Our comprehensive benefits package includes a 401(k) plan with the maximum legally permitted employer match. Employees enjoy top-tier insurance coverage, encompassing health, dental, hospital, accident, and vision plans. For candidates needing to relocate to NYC, we provide relocation reimbursement. You'll thrive in our fast-paced learning environment where professional growth is constant.We embrace a flexible hybrid model, typically in-office 3–4 days per week. If you’re interested in the role but aren’t sure whether you’re a good fit, we’d still like to hear from you.

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About the role💥 Your impactOnyx is a popular open source project with hundreds of thousands of users. The project has over 10K stars and over 3K community members across Slack and Discord (these stats may already be out of date when you read this). You’ll have the opportunity to build in the open and your work may be used by millions of people in the future.💡 About the roleOnyx is the knowledge layer on top of LLMs. Help us improve our agent and knowledge retrieval capabilities to push the frontier on unsolved problems like multi-hop QA, needle in haystack, aggregation type RAG, etc. This is an in-person role based in San Francisco, CA.You’ll be:Evaluating and implementing LLM based knowledge graphs, advanced RAG approaches (StructRAG, etc.), LLM agents, advances in NLP, multi-modal transformers, advanced information retrieval algorithmsWorking on users’ experience with the platform through features like learn from feedback, search personalization, SME suggestion, etc.Build a semantic and programmatically useful understanding of the organization's priorities, projects, and people as additional signals to the answering capabilities of OnyxOwn the approach from inception to validation to production codeCollaborate with Founders and the Head of AI to shape and influence the direction of the product and contribute to the AI/ML engineering strategy🚀 You’ll be successful if you…Have 3+ years of AI/ML engineering experience building real-world applicationshave in-depth experience with PyTorch/Tensorflow, NLP models, and standard ML algorithmsAre up date with new advances such as open source/proprietary LLMs, RAG and agent-frameworksStrong software engineering background and capable of building backend features with web frameworks, ORMs and relational DBsExcellent communication skills and ability to collaborate with full stack roles⭐ Bonus pointsFamiliar with the full stack Typescript/React/NextJS, Python, PostgresInterested in writing technical blogs to establish Onyx is leader in the spaceAbout the interviewNon-technical Phone Screen (30 mins)ML Interview (45 mins)Practical Coding Interview (30 mins)Work Trial (3 days in person, fully covered + compensated)About OnyxOnyx is the open source GenAI platform connected to your company's docs, apps, and people. We ingest and sync from all sources of information (Google Drive, Slack, GitHub, Confluence, Salesforce, etc.) to provide a centralized place for users to ask about anything. Imagine your most knowledgeable co-workers, all-rolled into one, and available 24/7!We believe that every modern team will be adopting knowledge enhanced GenAI within the next 5 years and it is our goal to bring this technology to all the teams of the world.We raised a $10M seed coming out of YCombinator, backed by Khosla Ventures (early/seed backers of OpenAI, Doordash, GitLab, etc.) and First Round Capital (Notion, Square, Roblox, etc.). Our customers include of the best teams in the world like Netflix, Ramp, Applied Intuition and dozens of others. We also have incredible open source users like Roku, Zendesk, L3Harris and more.

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We are looking for a Member of Technical Staff who is skilled in computational biology and in machine learning. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. This is an opportunity to help shape and grow an organization that advances artificial intelligence and applies it to longstanding scientific challenges. In your role you will evaluate, apply and refine our proprietary generative models with the goal of designing new proteins that are functional in wet lab assays.Who you areYou are a scientific programmer. You have worked on notable science simulations or machine learning based projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues.You are a successful scientist. You have a PhD (or equivalent industry experience) in computational biology, bioinformatics, computer science, biochemistry, structural biology, physics, biophysics, bio/chem engineering, synthetic biology or a related field.You are an experienced molecular data analyst. As a data analyst, you use techniques from statistics, molecular dynamics and molecular visualization to generate insights on biomolecular problems.You are a skilful developer. You write software that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production-quality code.You are an owner. You have a proven track record of delivering successful commercial and / or academic research projects, demonstrated through publications, patents, and/or commercially impactful outcomes, as well as other contributions to the scientific community.You are mission driven and curious. You are passionate about making a positive impact on the world, whether it's for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear.You thrive in a dynamic environment. You work well in a fast-paced setting where goals must be achieved efficiently and urgently.What sets you apartYou have experience in protein design and bioinformatics. You have worked on ML-driven projects in biology or conducted large scale bioinformatics analysis.You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields.You have helped scale a young biotech before. You have worked in startups and helped the company grow.Your ResponsibilitiesEvaluate the capabilities of our proprietary generative AI models:Design evaluation strategies and benchmarks to continuously evaluate the performance progress of our models.Lead deep-dives on select biological and therapeutic applications. Use your insights to identify opportunities and risks.Compare our generative models against external technologies.Closely collaborate with machine learners, protein designers, and biologists to ensure the technical and biological relevance of our model evaluations. Feed back results via regular meetings and presentations.Incorporate and automate relevant evaluation strategies into our model training workflows.Use your insights to help improve our models:Leverage your analytical results to guide model performance improvements. Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.Implement and test ideas for model improvements, including finetuning on our own wet lab data and new architectural ideas or model features.Improve the way we apply our models:Use evaluation metrics to automatically optimize the way we apply our models, e.g. by identifying optimal sampling techniques and hyperparameters.Self development:Stay on top of the latest developments in ML.Gain a strong working understanding of protein and cell biology.Participate in knowledge sharing, e.g. organize and present at our internal reading group.Attend and present at conferences when relevant.ApplyWe offer strongly competitive compensation and benefits packages, including:Private health insurancePension/401(K) contributionsGenerous leave policies (including gender neutral parental leave)Hybrid workingTravel opportunities and moreWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.

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