Senior Machine Learning Scientist Jobs

Responsibilities: Annotate Case Report Form (acrf.pdf) following FDA/CDISC or sponsor guidelines. Develop SDTM specifications and generate SDTM datasets using SAS; Develop ADaM,specifications and generate ADaM datasets using SAS based on Statistical Analysis Plan; Develop Tables, Listings, Graphs, Patient Profile in support of the Clinical Study Report, Posters, Manuscripts; Develop ADaM data, Tables, Listings, Figures for Integrated Summary of Safety (ISS) and Integrated Summary of Efficacy (ISE) Create electronic submission packages to FDA, e.g., define.xml or define.pdf following FDA guidelines with no supervision. Expert-level in analyze information and develop innovative solutions to programming and data analysis challenges; Serve as point of contact (POC) of programming with statisticians for statistical input and analysis interpretation; Follow and reinforce regulatory agency requirements during daily job. Serve as a programming team lead and contribute to department initiatives. Provide guidance, mentoring, training for team members and help solve issues from cross-functional teams; Review draft and final production deliverables for project to ensure quality and consistency. Work with global team or sponsors to coordinate project deliverables, timelines and resources. Skills and Responsibilities: Bachelor’s/Master’s degree in Statistics, Mathematics, Computer Science, Electrical Engineering, Biotechnology or related scientific disciplines with 5+years of clinical programming experience. Proven knowledge and training in high level computing languages such as. SAS, C/C++, Java, R, Python, MATLAB and SQL. Database programming experience is a plus. Expert-level in decoding programming logic and assembling programming code based on logic provided and be able to explain to team members. Expert level in applying concept in Artificial Intelligence and Machine Learning in real world. In-depth knowledge of ICH, Good Clinical Practices, Clinical research, Clinical tria

Responsibilities: Annotate Case Report Form (acrf.pdf) following FDA/CDISC or sponsor guidelines. Develop SDTM specifications and generate SDTM datasets using SAS. Develop ADaM specifications and generate ADaM datasets using SAS based on Statistical Analysis Plan. Develop Tables, Listings, Graphs, Patient Profile in support of the Clinical Study Report, Posters, Manuscripts. Develop ADaM data, Tables, Listings, Figures for Integrated Summary of Safety (ISS) and Integrated Summary of Efficacy (ISE). Create electronic submission package to FDA, e.g., define.xml or define.pdf following FDA guidelines with minimum supervision. Proficient in analyze information and develop innovative solutions to programming and data analysis challenges; Support the point of contact (POC) of programming with statisticians for statistical input and analysis interpretation Follow and reinforce regulatory agency requirements during daily job. Serve as a programming team lead and contribute to department initiative. Provide guidance, mentoring, training for team members and help solve issues from cross-functional teams. Review draft and final production deliverables for project to ensure quality and consistency. Skills and Qualifications: Bachelor’s/Master’s degree in Statistics, Mathematics, Computer Science, Electrical Engineering, Biotechnology or related scientific disciplines with at least 4+ years of clinical programming experience. Proven knowledge and training in high level computing languages such as. SAS, C/C++, Java, R, Python, MATLAB and SQL. Database programming experience is a plus. Proficient in decoding programming logic and assembling programming code based on logic provided and be able to explain to team members. Proficient in applying concepts in Artificial Intelligence and Machine Learning in the real world. In-depth knowledge of ICH, Good Clinical Practices, Clinical research, Clinical trial process and related regulatory requirements and terminology. Good understa

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! Why this role? 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, Pa

ROLE SUMMARY As an AI-enabled strategic scientific leader, you will partner with Oncology Research Leadership to integrate AI-driven strategies that will drive data-informed decision-making across our Oncology Research pipeline. As the AI Portfolio Lead, you will bridge cutting-edge AI/advanced analytics with deep Oncology R&D expertise to guide our portfolio strategy. Working as an individual contributor reporting into the Head, Portfolio Strategy and Program Management, you will analyze and continuously assess Oncology Research projects using AI-driven insights (predictive models, scenario simulations, competitive intelligence) and propose actionable strategies to Oncology Research Leadership. This role is science-focused and spans across discovery and preclinical stage programs, ensuring that our project teams pursue the most promising scientific approaches and mechanisms of action. Your work will directly inform pipeline prioritization and resource allocation decisions, enhancing the quality and objectivity of governance deliberations with robust data. ROLE RESPONSIBILITIES Portfolio Analysis and Insights: Continuously analyze the oncology Research portfolio (ESD through Preclinical) using advanced AI/ML tools and analytics to evaluate each program’s scientific strength, probability of success, and strategic portfolio fit per disease area strategies. Strategy Recommendation: Develop and propose data-driven portfolio strategies (at both project and portfolio levels) to senior leaders and Research governance committee. Use scenario analysis and predictive modeling to highlight optimal project prioritization, pipeline balance, and resource allocation scenarios. AI-Enabled Decision Support: Integrate AI-derived insights (e.g. machine learning predictions, knowl

About the Team Our Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety. About the Role Providing access to frontier AI systems raises complex questions around dual-use science and catastrophic risk. How should models respond to requests involving chemical synthesis, biological experimentation, or pathogen research? Where is the boundary between legitimate scientific inquiry and information that could enable misuse? How do we design policies that meaningfully reduce risk without unnecessarily restricting beneficial research? This is a senior role in which you’ll help shape policy creation and development at OpenAI for addressing biological and chemical risks. You will develop structured policy frameworks and taxonomies to guide safe model behavior. This role sits at the intersection of biosecurity expertise, AI safety research, and policy design. You will help ensure that frontier AI systems can support beneficial life sciences research, such as drug discovery, public health, and biosafety, while reducing the risk that these capabilities could be misused. Our relevant publications: Preparedness framework Preparing for future AI capabilities in biology Safety evaluations hub OpenAI GPT5 System Card Evaluating Fairness in ChatGPT Improving Model Safety Behavior with Rule-Based Rewards OpenAI Model Spec Your Responsibilities: Design and maintain model policies governing chemical and biological risk, defining how models should safely handle dual-use scenarios. Develop structured taxonomi

Senior Machine Learning Developer Location: Montreal, Quebec, Toronto, or Ontario About Numa Numa is building the platform to power AI-native dealerships, rearchitecting automotive service and sales with advanced AI agents that automate customer interactions, streamline operations, and reimagine how dealerships work. Numa integrates AI into every aspect of dealership functions—from rescuing customer calls and voicemails that generate more revenue, to reducing customer resolution times that drive overall customer satisfaction (CSI), to improving dealership team productivity and accountability. Numa has raised $50 million from leading investors (Google, Threshold, Costanoa, Mitsui, and Touring Capital). The Role We’re hiring a Senior Machine Learning Developer to build and ship ML/AI systems that interact with real customers thousands of times a day. Our voice agents book service appointments, rescue missed calls, and route callers through natural conversations. You’ll work across products and platforms. You’ll ship AI features including prompts, agents, tools, and production ML models, while building the evaluations and tooling that help teams ship with confidence. You’ll also contribute to our ML platform, including model serving, LLM infrastructure, and production observability. At Numa, we believe great ML is about more than building bigger models. It’s about knowing whether a change is good enough to ship. Our evaluation-first approach makes that measurable in CI and production. What You’ll Do Build conversational AI systems for phone and SMS that understand customer needs, take action, and know when to act autonomously Develop tooling such as memory, knowledge graphs, and validated customization that help agents reason and adapt to dealership needs Train, evaluate, and deploy ML models using Ray Serve and Dagster for prediction, classification, ranking, and capacity forecasting, and keep them healthy in production Create offline and online evalua

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Senior Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Design, develop, and implement recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 3+ years of industry experience building production Machine Learning systems BS, MSc, or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine learning pipelines: data e

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 hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit 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 As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and

About Graphcore At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence. Job Summary As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field. The Team The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. We build reference applications, contribute to key software libraries e.g. optimising kernels for efficiency on our hardware, and collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications. If you're excited about advancing the next gen

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Fraud Data team at Plaid builds the machine learning systems that power Plaid’s fraud detection products, leveraging insights from across Plaid’s network to help identify and stop fraud before it happens. Our team works across the full data science and machine learning lifecycle—from discovering new signals and experimenting with models to deploying and optimizing them in production. We continuously learn from real-world model performance and customer feedback to improve our systems and develop new ways to protect customers and consumers from evolving fraud threats. As a Senior Machine Learning Engineer on Plaid's Fraud Data team, you will develop models that improve fraud detection for our customers. You will identify predictive patterns in Plaid's network data and lead projects from initial experiments through model deployment and ongoing improvement. Investigate fraud patterns and model errors to identify new signals, improve detection, and expand coverage across customers and use cases. Develop training datasets and predictive features, addressing challenges such as incomplete labels, class imbalance, data leakage, and changing fraud behavior. Design, train, and tune model

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers. As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You’ll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You’ll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions. Responsibilities: Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment. Solve complex technical challenges at the intersect

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview As a machine learning engineer in the Economics team, you will build state-of-the-art systems that blend rigorous economic thought with sophisticated machine learning algorithms to tackle some of the company's most challenging problems. Working in a horizontal team, you will have the opportunity to collaborate closely with partners across multiple functions to operate on a highly diverse set of problems, contributing both economic and engineering expertise in a fast-paced environment filled with exciting opportunities for technically-minded economists. The Economics team at Instacart works on a range of interesting and challenging problems across our platform, from aligning the incentives in our multi-sided marketplace to analyzing the role of prices and product placement in our customers' decision-making. Some of the core areas of focus for our team inclu

At Bazaarvoice, we create smart shopping experiences. Through our expansive global network, product-passionate community & enterprise technology, we connect thousands of brands and retailers with billions of consumers. Our solutions enable brands to connect with consumers and collect valuable user-generated content, at an unprecedented scale. This content achieves global reach by leveraging our extensive and ever-expanding retail, social & search syndication network. And we make it easy for brands & retailers to gain valuable business insights from real-time consumer feedback with intuitive tools and dashboards. The result is smarter shopping: loyal customers, increased sales, and improved products. The problem we are trying to solve : Brands and retailers struggle to make real connections with consumers. It's a challenge to deliver trustworthy and inspiring content in the moments that matter most during the discovery and purchase cycle. The result? Time and money spent on content that doesn't attract new consumers, convert them, or earn their long-term loyalty. Our brand promise : closing the gap between brands and consumers. Founded in 2005, Bazaarvoice is headquartered in Austin, Texas with offices in North America, Europe, Asia and Australia. It’s official: Bazaarvoice is a Great Place to Work in the US , Australia, India, Lithuania, France, Germany and the UK! Senior ML/AI Engineer Full-Time Who we are: In an era of rising AI agents and consumer skepticism, Bazaarvoice sources, verifies and amplifies authentic consumer ratings, reviews and visual content at scale, making your products discoverable, trusted, and chosen. We source, verify, and amplify authentic product ratings, reviews, photos, and videos at scale. Driving reach, traffic, and conversion. We make products discoverable, trusted, and chosen, by shoppers and by AI. We are the world’s most trusted network of authentic consumer voices. Where AI/ML is key: Our solutions enable brands to co

Senior Machine Learning Engineer — NY - New York. Apply via Workday.

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Digital Twin Platform team at Instacart is on a mission to understand exactly what is on store shelves at all times — bringing the precision and depth of a smart warehouse to every local grocery store across North America. Inventory estimates power some of the most critical products at Instacart, from search to logistics, and this team sits at the center of it all. Operating like a startup within a larger company, the team drives the end-to-end shelf data supply chain: ingesting data from retail partners, actively collecting novel inventory observations, developing sophisticated models, and integrating those outputs into live products at scale. We are looking for a Senior Machine Learning Engineer to help build the next generation of platforms for understanding, observing, and predicting inventory levels and in-store stocking dynamics in real time. In