Data Scientist - Agentic AI

About SimpliSafe SimpliSafe stands at the forefront of innovation within the home security sector, committed to ensuring that every household can feel secure. Our mission revolves around delivering accessible and thorough security solutions by designing user-focused products that empower families to safeguard what they cherish the most. We foster a collabora…

Join the Innovative Team at SunoAt Suno, we are not just a music company; we are a creative powerhouse dedicated to igniting imagination through the magic of sound. Harnessing the capabilities of the world’s most advanced AI music model, we provide an exceptional creative platform, including our groundbreaking generative audio workstation, Suno Studio. We believe in empowering everyone—from shower singers to seasoned artists—to create, share, and discover music, making musical expression accessible to all.Role OverviewWe are seeking passionate early members of our research team to collaborate closely with our founding members. You will play a pivotal role in shaping the future of our machine learning initiatives by making critical technical decisions on the development and deployment of our cutting-edge ML models, boasting an H100/scientist ratio exceeding 100x.Explore the Suno job posting here!

Join Zoox as a Senior Data Scientist specializing in Machine Learning for Perception. In this pivotal role, you will leverage your expertise to develop advanced machine learning algorithms that enhance perception systems. Your contributions will directly impact the design and functionality of autonomous vehicles, driving innovation in the field.

Join Lendbuzz, where we champion personalized and equitable financial opportunities. Our cutting-edge technology empowers underserved borrowers to gain better access to credit. We foster a culture that celebrates diversity and encourages independent and critical thinking among all our team members.We are seeking a passionate Machine Learning Scientist dedicated to creating impactful solutions in a collaborative and dynamic team environment. The ideal candidate will have a robust background in software development, exemplary data analysis and communication skills, accompanied by a profound knowledge of machine learning and statistical methods.

About the RoleWe are seeking a talented Data Scientist to take charge of ensuring the quality, reliability, and trustworthiness of our clinical AI outputs. In this pivotal role, you will develop systems that help our AI recognize its limitations, including the creation of evaluation frameworks, calibrated confidence scoring, and automated quality assurance protocols that healthcare professionals can rely on.Key ResponsibilitiesDesign and deploy automated evaluation pipelines to assess the quality, accuracy, and safety of AI outputs at scale.Develop systems for uncertainty quantification where confidence scores are meaningfully aligned with accuracy.Create comprehensive evaluation frameworks that integrate automated assessments with clinician-validated test cases.Implement continuous feedback mechanisms to enhance model outputs based on validation signals.Establish scalable quality gates to identify errors before they impact end users.Contribute to efforts focused on model alignment and fine-tuning.

Become a Force for Good at Axon.At Axon, our mission is to Protect Life. We are dedicated explorers, tackling society’s most pressing safety and justice challenges with our innovative ecosystem of devices and cloud software. Our collaborative culture fosters openness and empathy, drawing upon diverse perspectives from our customers, our communities, and each other.Life at Axon is dynamic, challenging, and deeply rewarding. Here, you will take ownership and drive meaningful change while growing alongside a purpose-driven team.Your ImpactWe are looking for exceptionally talented and forward-thinking Machine Learning Scientists to join our AI team, specializing in AI applications such as Large Language Models (LLM) and Computer Vision in Cloud, Devices, and Robotics. As a pivotal member of our research and development initiative, you will significantly contribute to the advancement of cutting-edge technologies like LLMs, Multimodal Large Language Models (MLLMs), Computer Vision, and Generative AI (GenAI) for law enforcement and beyond. You will work collaboratively with cross-disciplinary teams to design, develop, and implement innovative LLM, MLLM, and CV models and algorithms, enabling intelligent reasoning, perception, and comprehension of multimodal data.What You’ll DoLocation: Available in any city with an Axon Engineering Hub in the US, Vietnam, or EU (see https://www.axon.com/company)

JOB SUMMARYJoin our innovative team at Iambic Therapeutics as a Machine Learning Software Engineer (I/II). In this dynamic role, you will develop, deploy, and manage machine learning systems that significantly contribute to our drug discovery initiatives. Collaborate with a diverse team to optimize ML lifecycle workflows, enhance GPU-accelerated application deployment, and work closely with ML scientists to convert models into robust, scalable software solutions. This hybrid position is based in our Boston, MA office.KEY RESPONSIBILITIESDesign and implement production-grade ML workflows, ensuring strong observability and CI/CD practices.Deploy GPU-accelerated ML services using contemporary tools and cloud orchestration.Work collaboratively with ML scientists and cross-functional teams to gather requirements, define milestones, and integrate features into existing workflows.Conduct code reviews and mentor team members on best practices in software engineering and MLOps.QUALIFICATIONSEngineer I: At least 5 years of relevant experience with a Bachelor’s degree in a scientific field; or 3 years with a Master’s degree; or equivalent experience.Engineer II: 8+ years of relevant experience with a Bachelor’s degree in a scientific field; or a PhD with 3+ years of experience; or equivalent experience.Proficient in modern Python development, including packaging, type hints, testing, and performance optimization, with experience in creating production services and libraries.Hands-on experience with ML model lifecycle and associated tools (e.g., PyTorch, Hugging Face, vLLM/Triton/ONNX Runtime); data tools (e.g., Pandas, Arrow, S3, Parquet); and workflow orchestration (e.g., Prefect, Airflow, Luigi).Experience with cloud deployment (AWS preferred), including containerization, Infrastructure as Code (IaC), and GPU workload considerations.Experience in scientific domains or drug discovery is a plus; the ability to collaborate effectively with scientists and communicate across disciplines is essential.ABOUT IAMBIC THERAPEUTICSIambic Therapeutics is a pioneering clinical-stage life sciences and technology company, dedicated to developing groundbreaking medicines through its AI-driven discovery and development platform. Founded in 2020 and headquartered in San Diego, we are committed to leveraging advanced technology to transform healthcare.

At WHOOP, we are revolutionizing health and fitness with our state-of-the-art wearable technology, dedicated to enhancing human performance and extending healthspan. Our innovative approach enables members to gain profound insights into their bodies, behaviors, and daily activities, empowering them to make healthier choices and achieve peak performance.We are on the lookout for a Senior Machine Learning Engineer to join our dynamic Foundation AI team. This team is responsible for developing the multimodal foundation models that drive WHOOP’s next generation of intelligent, personalized, and health-optimizing solutions. These models seamlessly integrate data from wearable sensors, linguistic inputs, biomarkers, clinical data, and self-reported metrics to build scalable AI systems that accurately understand human physiology and behavior.In this pivotal role, you will be a key individual contributor leading the research, development, and implementation of large-scale multimodal models. You will work collaboratively with data scientists, ML engineers, and cross-functional partners to advance the frontiers of deep learning and ensure that our models provide significant value to WHOOP members.

Company Overview: FL106 Inc. is an innovative biotechnology firm in its early stages, dedicated to the development of groundbreaking drug delivery systems. Supported by Flagship Pioneering, FL106 aims to transform cutting-edge scientific platforms into practical solutions that significantly enhance patient care. Position Overview: We are on the lookout for a driven and enthusiastic Senior Scientist specializing in computational protein design, with a strong foundation in AI and machine learning tools specifically for antibody and protein design. The selected candidate will lead the creation of novel protein-based delivery systems while collaborating closely with experimental teams to refine and validate computational designs. This role is perfect for someone who thrives in a dynamic, entrepreneurial environment and is eager to influence the scientific direction of FL106, working alongside the visionary founders of Flagship Pioneering. Key Responsibilities: Lead the computational protein design efforts utilizing AI and machine learning techniques. Collaborate with Pioneering Intelligence at Flagship to explore and integrate advanced ML models into FL106’s design framework. Advance antibody engineering and de novo antibody design strategies. Work closely with experimental scientists to test and iterate on protein constructs. Innovate new functionalities within protein scaffolds using structural modeling, rational design, or directed evolution methodologies. Stay updated on advancements in computational protein design to guide strategic decisions in protein engineering. Shape the strategic vision of the computational team at FL106, positioning our design platform at the forefront of scientific advancement. Establish and nurture external research collaborations with academic and commercial entities. Present research findings to scientific teams and Flagship Pioneering management. Essential Qualifications: Ph.D. in computational protein design, protein biochemistry, computational biophysics, computational biology, physics, or a related discipline, with a minimum of 2 years of industry research experience. Proficient in computational protein modeling and design, with a solid understanding of structural biology and biophysics. Extensive experience with machine learning tools for computational protein design such as AlphaFold, RosettaFold, ESMFold, ProteinMPNN, RFDiffusion, Chroma, IgFold, and DeepAb. Demonstrated experience in antibody engineering and design is highly valued. Strong collaborative skills and the ability to thrive in a fast-paced startup environment.

Join the Harvard Business School AI Institute as a Senior Data Scientist, where you will leverage cutting-edge AI technologies to drive innovative projects and contribute to groundbreaking research. You'll collaborate with a talented team of data scientists and researchers, working on complex data challenges that impact the business landscape.

About Air Space IntelligenceAt Air Space Intelligence (ASI), we are at the forefront of mission-critical technology that transforms decision-making across the aviation, defense, energy, and critical infrastructure sectors. Supported by leading investors such as Andreessen Horowitz, Spark Capital, and Renegade Partners, ASI empowers organizations to achieve operational decision superiority—reducing days of analysis into mere seconds of actionable insights. Join us as we redefine the limits of possibility.Your Role:As a vital member of our engineering team, you will be responsible for designing and deploying robust production-grade systems that seamlessly integrate machine learning models into scalable software pipelines. You will develop and implement features that utilize machine learning to address real-world optimization and prediction challenges, leveraging cutting-edge technologies such as Kubernetes, AWS, and MLOps tools. Your approach will reflect a software engineer's mindset—focusing on reliability, maintainability, and high performance at scale.Our Core Values:Expertise in Python, along with experience in production machine learning tools and frameworks like TensorFlow, PyTorch, and scikit-learn.Hands-on experience with large language models (LLMs) in production settings, encompassing prompt engineering, fine-tuning, retrieval-augmented generation (RAG) systems, and frameworks such as LangChain.Deep understanding of data structures, algorithms, and software engineering principles.Familiarity with classical machine learning, deep learning with an emphasis on transformer architectures, and MLOps methodologies.Experience in building and maintaining scalable, reliable machine learning systems with comprehensive data pipelines, including proficiency with Apache Beam, MLflow, and similar tools.Dedication to high-quality machine learning engineering practices, including data versioning, experiment tracking, model governance, and automated testing pipelines.A preference for simplicity and clarity when tackling complex challenges.An inquisitive mind and eagerness to collaborate with others.Strong communication skills and the ability to work effectively across cross-functional teams.Our Hiring Philosophy:We view the interview process not merely as a screening test but as an opportunity to simulate what it will be like to work together. Our hiring process is tailored around you.

About Us At PathAI, our mission is to revolutionize patient care by enhancing diagnostic accuracy through AI-driven pathology solutions. Our platform is designed to significantly boost the precision of disease diagnoses and the effectiveness of cancer treatments by utilizing cutting-edge machine learning and artificial intelligence technologies. With a proven history of implementing AI algorithms in histopathology across various settings, including translational research, pathology laboratories, and clinical trials, we emphasize rigorous scientific methodologies and thorough analyses in every project. Our diverse team, united by a shared passion for tackling complex problems, is dedicated to making a meaningful impact on patient outcomes. Your Role We are on the lookout for talented Machine Learning Engineers (Applied Research & Model Development) to join our innovative team. In this role, you will engage with various departments, including biomedical data science, product development, translational research, MLOps, and platform engineering, to advance our machine learning capabilities and enhance patient care through our AI products and services. Key Responsibilities Design, implement, and launch machine learning models for both research and product development initiatives. Work collaboratively with cross-functional teams, including scientists, engineers, and product stakeholders, to translate clinical and biological requirements into scalable machine learning solutions. Participate in experimental design and analysis, including ideation, documentation, and reporting processes. Contribute to team knowledge sharing initiatives such as design reviews, journal clubs, and discussions on machine learning best practices and governance. Enhance machine learning pipelines and infrastructure in collaboration with MLOps and platform engineering teams.

LOCATION: This position can be based anywhere in Canada, with a preference for candidates in the eastern or central time zones to collaborate effectively with our teams in the US, Europe, and India.ABOUT THE ROLEWiser Solutions is on the lookout for a Principal Machine Learning Engineer to steer and implement our AI and data science initiatives. This senior technical leadership role requires a unique individual who possesses extensive knowledge in machine learning, data science, and production engineering, coupled with the business insight needed to transform intricate capabilities into tangible customer value.In this role, you will serve as the leading technical authority on AI at Wiser. Your responsibilities will include defining the architectural vision, showcasing our capabilities to clients and partners, and delivering production systems that yield measurable business results. This position demands an individual who can seamlessly navigate between strategic planning and hands-on execution, capable of engaging with executives one day and troubleshooting production pipelines the next.We are fostering an AI-driven engineering culture at Wiser, where AI tools and methodologies are integrated into our workflows—not just our products. We seek a Principal AI Engineer who not only develops AI solutions but also exemplifies AI-enhanced working practices and aids the broader engineering team in their adoption. If you’re passionate about the transformative power of AI in software development and actively embrace this shift in your daily work, we want to hear from you.Key ResponsibilitiesStrategic LeadershipCollaborate with product and business leadership to define and refine Wiser's technical AI and data science strategy.Communicate Wiser's AI capabilities to clients, partners, and advisors, outlining our approach, roadmap, and unique value proposition.Spot high-impact opportunities where AI can effectively address client challenges or provide competitive advantages.Set technical standards, patterns, and best practices that guide engineering decisions across the organization.Technical ExecutionDesign and develop production AI systems, including applications for LLM, RAG pipelines, semantic search, and traditional ML models.Create rigorous evaluation frameworks, experimentation methodologies, and monitoring systems that ensure AI solutions deliver reliable, measurable outcomes.Integrate classical data science techniques (statistical modeling, experimentation design, feature engineering) with modern generative AI methods.Oversee the technical quality of AI systems end-to-end, from data pipelines and model deployment to production observability.Cross-Functional CollaborationWork alongside product management to translate business needs into technical solutions and validate them against customer expectations.Guide and uplift the AI/data science team (3-5 engineers), enhancing the technical proficiency across the board.

Join our innovative team at Flagship Pioneering Inc. as a (Senior) Machine Learning Engineer, where you'll be at the forefront of developing cutting-edge artificial intelligence solutions. In this role, you will leverage your expertise in machine learning algorithms and data analysis to drive impactful results across various projects. Collaborate with a diverse team of scientists and engineers to create scalable models that can be implemented in real-world applications.

Join the innovative Offline Driving Intelligence (ODIN) team at Zoox, where we harness cutting-edge AI technologies to develop algorithms that enhance our understanding of the world around us. Our focus is on utilizing large models primarily in offline environments to create impactful solutions for our self-driving robot, facilitating safe and efficient navigation through complex settings.As a vital member of the ODIN team, you will be tasked with the development of advanced multimodal large language models that significantly improve environmental comprehension. Your role will involve fine-tuning these models for off-vehicle analysis, collaborating closely with the onboard engineering team to implement solutions that enable our robotaxi platform to swiftly identify hazards and interpret driving restrictions with minimal latency. Working alongside a team of esteemed engineers and researchers, you will leverage high-quality sensor data and state-of-the-art infrastructure to validate your algorithms in real-world scenarios, making a direct contribution to the productivity, safety, and capabilities of Zoox's autonomous systems.

Join Our Team at Motional: As a Senior Machine Learning Engineer specializing in ML Planning, you will collaborate with top-tier machine learning engineers and research scientists to revolutionize the future of self-driving vehicles. Your work will contribute to creating a positive social impact by enhancing the technology that interprets complex driving environments and devises safe, efficient driving strategies for our robotaxi fleet.Your Responsibilities:Lead the design and execution of innovative experiments, leveraging insights from cross-functional teams of machine learning engineers.Prototype and implement advanced metrics to assess the performance of our behavioral models across diverse scenarios and capabilities of our robotaxi.Ensure timely deployment of significant model updates, analyzing both offline and on-road evaluation results.Stay abreast of industry trends and propose novel architectures and network designs informed by the latest research.Maintain a robust and high-quality training and evaluation codebase, focusing on dataset generation and assessment.

About UsCyvl is an innovative tech startup based in Boston, reshaping the way governments map and manage their transportation infrastructure. Our cutting-edge hardware and software solutions utilize advanced 3D mapping sensors to collect LiDAR, imagery, and GPS data, seamlessly integrated into our clients' vehicles. This data is processed through our AI-driven cloud pipelines to produce actionable geospatial insights that optimize city operations, saving time, money, and resources.At Cyvl, our mission is to empower governments in constructing and maintaining public infrastructure they can be proud of. We accelerate decision-making through our sensors and Infrastructure Intelligence Platform. This role is pivotal for our intelligence extraction process, responsible for transforming millions of street-level images and dense LiDAR point clouds into structured, queryable knowledge about the physical realm.We are a dynamic and rapidly growing team that believes in addressing real-world challenges with authenticity, simplicity, and courage. Each team member is empowered to take initiative, achieve results, and make a lasting impact on the communities we serve.

The Machine Learning Observability team at Datadog is at the forefront of developing innovative tools designed to monitor, interpret, and enhance AI systems deployed in production environments, with a special focus on Large Language Models (LLMs) and generative AI technologies. Our solutions provide comprehensive and scalable observability for AI workloads, including drift detection, model evaluation, and behavior tracing, empowering our clients to deploy AI confidently. As a Staff Software Engineer, you will be instrumental in driving the development of new features and core capabilities within Datadog’s LLM Observability product. You will influence product strategy, lead experimental initiatives, and leverage your extensive knowledge of AI systems and software engineering to tackle complex challenges in the rapidly evolving AI domain. Your contributions will have a significant impact on how our customers monitor, diagnose, and optimize LLM-powered applications in production. Join us in creating the essential tools that ensure AI systems are observable, comprehensible, and dependable in real-world applications. At Datadog, we value our office culture which fosters relationships, collaboration, and creativity. We operate within a hybrid work model to enable our Datadogs to achieve a work-life balance that suits them best.

Mission Overview: At Motional, we are revolutionizing the way autonomous vehicles extract vital insights from extensive multimodal sensor data. Our advanced autonomous driving architecture relies on identifying rare edge cases, long-tail scenarios, and significant model inaccuracies. Our innovative framework, Omnitag, serves as the driving force behind this data discovery. In your role as a Senior Machine Learning Engineer within the Data Mining team, you will be tasked with creating the "Brain" of this framework: designing large-scale multimodal Teacher models that interpret the world and refining them into hyper-efficient Student models capable of analyzing exabytes of data in near real-time. You will operate at the crossroads of large-scale representation learning, retrieval optimization, and reasoning systems. Your contributions will profoundly impact how we encapsulate knowledge into streamlined encoders for rapid searches, as well as how we utilize reinforcement learning to enhance data discovery processes and intelligent querying. By developing smarter mining tools, you will expedite the entire model enhancement lifecycle for teams engaged in post-training evaluations, error diagnostics, and dataset refinement.