Ml Applied Research Manager Jobs

P-1408 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2026, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For BS+ (M.S. or PhD preferred) in Computer Science, or a related field. 10+ years experience developing search relevance systems at scale in production or in high-impact research environments. Experience applying LLM to search relevance Experience in one or more of the following: Query understanding NLP Text mining Recommendations Personalization Discovery Conversational AI Strong understanding of computer science fundamentals. Contributions to well-used open-source projects. Why Join Us? At Databricks, w

P-926 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking multiple senior engineers to drive enhancements to our Search Quality. In 2026, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For BS+ (M.S. or PhD preferred) in Computer Science, or a related field. 5+ years experience developing search relevance systems at scale in production or in high-impact research environments. Experience applying LLM to search relevance Experience in one or more of the following: Query understanding NLP Text mining Recommendations Personalization Discovery Conversational AI Strong understanding of computer science fundamentals. Contributions to well-used open-source projects. Why Join Us? At Databricks, we are building state-of-the-art AI solutions that red

Position Overview As a Senior Staff Software Engineer on Diligent's Platform AI team, based out of our technical center of excellence in Vancouver, you will drive the architecture and technical direction of the services that bring AI research and models into production across Diligent's global product suite. You will partner with AI researchers, product managers, and Staff Engineers as peers — leading through influence across the Platform AI organization rather than through reporting authority, on secure, scalable AWS Serverless solutions that translate ML and LLM research into commercial-quality, production systems. Key Responsibilities Drive technical direction and architecture for ML/LLM systems across multiple AI platform teams, partnering with Staff Engineers rather than managing ICs in isolation. Design secure, scalable, fault-tolerant AI/ML solutions using AWS Serverless technology — event-driven, highly observable, with infrastructure as code. Evaluate and prototype new AI technologies (LLM frameworks, model providers, agentic tooling) to guide build-vs-buy decisions across the organization. Serve as the go-to contact for architecture problems and questions across the Platform AI org, and regularly present and guide architecture discussions department-wide. Mentor Staff Software Engineers and Applied Scientists through constructive code review and design partnership. Collaborate with Applied Scientists and Product teams to productize AI capabilities, translating multi-quarter AI strategy into execution roadmaps and representing engineering's perspective to senior leadership. Design, build, and scale search and retrieval systems — including OpenSearch and semantic/vector search — that power discovery, retrieval-augmented generation, and other AI-driven product features. Lead through ambiguity, helping teams navigate undefined problems to successful delivery. Required Experience/Skills 10-15+ years of professional experience developing and owning high-scale, s

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with petabyte-scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. As a PhD Machine Learning Engineer Intern on our Applied AI team, you'll take on an open research problem tied to product experiences used by millions of riders. Working closely with a Staff ML Engineer mentor, you'll scope the problem, develop and evaluate new methods on real data, and take the work far enough that it can be shared with the research community, with the goal of a paper submission to a top ML venue. If you are a PhD student who enjoys turning open-ended research questions into working systems, and you want your research to be tested against real users and real data, this opportunity is for you! Responsibilities: Own a research project from start to finish: frame the problem, review related work, propose new methods, and design rigorous offline and online evaluations Design, build, train and test ML models in areas such as reinforcement learning, sequential decision-making, personalization Write production-quality code that turns research prototypes into working pipelines on Lyft's data and ML infrastructure Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame research questions within the business context Analyze experimental and observational data, and communicate findings clearly to both technical and non-technical aud

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values . This position is based out of our India Development Center in Hyderabad. Who we are looking for Join Truveta’s Intelligence Platform and Applications (IPA) team to build the next wave of healthcare AI — developing adaptive agentic systems and fine-tuned foundation models that continuously learn, reason, and accelerate real-world impact. Guided by Truveta’s mission of Saving Lives with Data, you’ll help transform how health data becomes intelligence, powering breakthroughs that enable researchers, clinicians and operational managers to make data-driven, proactive, and impactful decisions. We firmly believe that patients, doctors, and medical researchers deserve to benefit from the artificial intelligence revolution that is transforming productivity, creativity, and communication. You’ll help shape the AI capabilities that make healthcare more intelligent, efficient, and equitable — driving real-world impact across research, care delivery, and patient outcomes. If you’re seeking a sense of purpose and are motivated to advance how AI supports learning, decision-making, and discovery in healthcare, you’ll find this an inspiring place to grow. We are seeking AI Engineers who thrive at the intersection of agentic and applied AI, machine learning, and large-scale engineering. You’ll blend ML craftsmanship with platform engineering excellence to create scalable, self-improving AI agents and models that learn from vast, diverse healthcare data and deliver meaningful insights through

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . As a Machine Learning Intern at Pinterest, you’ll apply machine learning and AI to product and engineering challenges. You’ll work with engineering, product and data teams to prototype, evaluate and improve ML-powered features and discovery experiences. Throughout your internship, you’ll contribute to real projects, learn how large-scale ML systems are developed and build practical skills with guidance from experienced engineers. What you’ll do: Own a scoped machine learning project from problem definition through experimentation, implementation and communication of results, with guidance from your manager and team Contribute to applied machine learning and AI research that informs Pinterest product experiences Collect, analyze and synthesize data to develop data-driven machine learning models Write clean, efficient and maintainable code, suppor

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . As a Machine Learning Intern at Pinterest, you’ll apply machine learning and AI to product and engineering challenges. You’ll work with engineering, product and data teams to prototype, evaluate and improve ML-powered features and discovery experiences. Throughout your internship, you’ll contribute to real projects, learn how large-scale ML systems are developed and build practical skills with guidance from experienced engineers. What you’ll do: Own a scoped machine learning project from problem definition through experimentation, implementation and communication of results, with guidance from your manager and team Contribute to applied machine learning and AI research that informs Pinterest product experiences Collect, analyze and synthesize data to develop data-driven machine learning models Write clean, efficient and maintainable code, suppor

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . As a Machine Learning Intern at Pinterest, you’ll apply machine learning and AI to product and engineering challenges. You’ll work with engineering, product and data teams to prototype, evaluate and improve ML-powered features and discovery experiences. Throughout your internship, you’ll contribute to real projects, learn how large-scale ML systems are developed and build practical skills with guidance from experienced engineers. What you’ll do: Own a scoped machine learning project from problem definition through experimentation, implementation and communication of results, with guidance from your manager and team Contribute to applied machine learning and AI research that informs Pinterest product experiences Collect, analyze and synthesize data to develop data-driven machine learning models Write clean, efficient and maintainable code, suppor

Senior Python / Agentic AI Engineer Capco: Where Innovation Meets Opportunity Capco is a global leader in consulting, uniquely positioned to drive innovation and transformation in the financial services industry. More than consultants, we are strategic partners and problem solvers for some of the largest organizations in Banking, Insurance, Investment Management, Data/Digital Transformation, Regulatory Compliance, and ICT Risk. Our business and technology professionals thrive in a dynamic environment where creativity, collaboration, and cutting-edge solutions are at the heart of everything we do. Experience the Capco difference and explore how you can shape your future with us at capco.com . Capco’s AI Lab The AI Lab is a cross-disciplinary research and engineering centre that translates advanced AI research into robust, deployable solutions for clients and internal products. It runs applied research (ML and agentic/LLM systems, planning, simulation and evaluation), rapid prototyping and production engineering (APIs, CI/CD, observability, data platforms and cost/latency optimisation), and rigorous evaluation and safety work (benchmarks, red-teaming, monitoring, governance and compliance). The lab also supports client engagements and internal innovation by building demonstrators and reference architectures, transferring technology to delivery teams, publishing technical learnings, and maintaining the shared infrastructure, tooling and best practices that enable reproducible, secure and scalable AI deployment. Responsibilities Design and implement scalable, production-grade Python services that leverage LLMs and Agentic architectures. Design and implement robust agent workflows and orchestration patterns to automate complex business processes in regulated enterprise environments. Build and maintain reliable AI-enabled backend systems , including orchestration layers, tool integrations, knowledge a

About the Team The Future of Computing Research team is an Applied Research team within the Consumer Devices group focused on developing new methods and models as we advance forward in our mission of building AGI that benefits all of humanity. As a Software Engineer on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities. About the Role We are looking for a Software Engineer to join our team to build tools and services that enable AI research, evaluation, and data generation workflows. The best work in this role will start with an ambiguous design question and turn it into working research systems. You will work closely with researchers, designers, and engineers to build the evaluation systems, synthetic data generation pipelines, review tools, and supporting platform services. The goal is to make these workflows easier to create, run, and trust without requiring bespoke engineering support for each new design concept. You will help ensure that research artifacts have a clear lifecycle, runs are reproducible and observable, and results provide useful evidence for product and model-training decisions while the underlying systems remain reliable and reusable. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Build web applications, APIs, data models, and backend services for AI research workflows. Build tools to author and manage evaluation tasks, rubrics, graders, suites, and rollout configurations, including workflows for publishing, versioning, auditing, and sharing research artifacts. Automate evaluation runs and generate useful reports for design, research, and engineering teams. Support synthetic data generation workflows for multimodal and conversational research, including tools that comb

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We're looking for a research engineer who believes that visual and spatial reasoning are core to fully unlocking the capabilities of LLMs. On the Vision team, you'll own the end-to-end process of creating training data and RL environments targeting visual knowledge work: identifying long-horizon and vision-heavy tasks, building evals, designing rewards, and scaling data. This is a unique role that combines applied research with hands-on data work. It's also highly collaborative — you'll partner with external vendors, pretraining, RL, and product teams to make sure the environments you build translate into real-world knowledge work capabilities. What you'll do: Own the data strategy for vision capabilities end-to-end, from building evals and scaling RL environments Manage technical relationships with external data vendors, including writing task specifications, evaluating visual data and annotation quality, and iterating on reward design Develop and improve QA frameworks that catch reward hacking and ensure environment quality at scale Run generalization experiments to measure how data strategy changes improve multimodal capabilities on held-out evaluations Partner with pretraining, RL, and product teams, and do the science that shows we’re all rowing in the same direction You may be a good fit if you: Have 7+ years of ML, computer vision, and software engineering experience through industry, academia, or other projects Have experience with reinforcement learning, reward design, or training data curation for large language or vision-language models Are familiar with the architecture, training, and operation of large visi

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role The Data team manages the complete lifecycle of data for researchers - from sourcing and large-scale processing to delivering datasets that power our models. Data sits at the heart of our Research efforts and enables all other teams. As part of the Data team, you’ll work with over a million hours of video and audio data. This role exists at the intersection of applied research, data engineering, and ML infrastructure rather than being a traditional research position . You’ll build the world’s best human-centric data lake by collaborating closely with our model training teams. By understanding their requirements, you’ll extract new features and annotations that elevate our datasets. You should be passionate about enhancing model performance through high-quality, accurate datasets. Our infrastructure and pipelines are in great shape, and this role provides room to not only enhance them but also influence the team’s longer-term strategy. What we're looking for: A strong background in data-centric, applied Machine Learning, with hands-on experience improving model performance through data quality, curation, labeling, and evaluation rather than model architecture alone Experience working on the data la

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in ML and CV to make autonomous driving as seamless as possible. The Opportunity Would you like to be part of the ML Training platform team that enables autonomous driving, driving scenario understanding, learned planning and trajectories, large scale driving simulations and several other ML use cases at Zoox? You will get to work across all ML teams within Zoox - Foundation Models, Perception, Prediction, Planner, Simulation, Data Science, Collision Avoidance, etc. and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. The ML Training platform team builds and operates the core part of the ML platform that powers model training at scale. We are responsible for developing and operating ML tools, deep learning frameworks, and distributed model training infrastructure to support foundational models and reinforcement learning. This team also owns the model repository and model lifecycle management tools used by our applied research teams for in- and off-vehicle ML use cases. You will play a crucial role in reducing the time it takes from ideation to productionization of cutting-edge AI innovation. This team has a lot of growth opportunities as we expand our robotaxi deployments and venture into new ML domains. In this role, you will: Build the Zoox Training framework leveraged by all ML teams within Zoox. This framework needs to be highly scalable, reliable, and efficient. Design, implement, and operate a robust and efficient ML platform to enable the training, validation, serving, and monitoring of ML models. Co

RDQ127R59 Summary As a Senior Applied ML Engineer on the Applied AI team at Databricks, you will use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure. Your work will span the entire stack—from cluster management down to query compilation. You will solve complex, high-impact engineering problems to deliver highly optimized, cost-effective workloads for our customers. Impact You Will Have Accelerate Serverless Growth: Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques. Build Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support Shape Strategy: Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks. Drive Deployment: Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency. Scale Infrastructure: Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems to help scale Innovate: Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments. Minimum Qualifications Education: Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc). ML Experience: Strong background in building, training, and deploying machine learning models in production. Infrastructure Knowledge: Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks. Core Coding: Proficiency in Python, Scala, or Java. Preferred Skills Advanced Education: PhD in AI, Data Science, or a related technical discipline. Industry Experience: 4+ years of machine learning engineering experience in high-velocity, high-growth environment. Systems Domain:

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 , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We are seeking an experienced and proactive Security Engineer to help us build, maintain, and continuously improve the security posture of our rapidly growing ML infrastructure platform. As one of the first dedicated security hires at Baseten, you will work cross-functionally with engineering and operations teams to ensure we’re meeting the highest standards of confidentiality, integrity, and availability. You’ll have an opportunity to shape our security strategy and best practices from the ground up, influencing the way our platform handles sensitive data for both internal and external stakeholders. RESPONSIBILITIES Security architecture and design: Collaborate with engineering teams to design and implement secure systems and infrastructure, including cloud (AWS/GCP) environments and container orchestration platforms. Vulnerability management: Lead proactive vulnerability assessments, pen tests, and remediation efforts to ensure our products and infrastructure remain secure. Incident response: Develop and maintain incident response processes, including detection, analysis, containment, eradication, and post-incident reviews. Identity and access management (IAM): Oversee IAM strategies and tools to ensure the right people have the right level of access to our systems and data. Security compliance and audits: Work closely with operations to ensure compliance with relevant standards (e.g., SOC 2, ISO 27001) and as