Senior Ml Science Manager Jobs

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Customer Experience Engineering Team builds the internal and external technologies that scale Snowflake’s global support and sales organizations. We empower our technical experts by providing the advanced tools they need to resolve complex issues and drive customer success. Our team specializes in software engineering, data-driven decisions, ML, and LLM-based solutions . We build production-grade systems to automate manual processes and augment the capabilities of our technical staff. Our current focus includes: LLMs : Developing and deploying LLM and agent-based architectures for streamlining troubleshooting Scalable Evaluations : Implementing large-scale evaluations to ensure the quality and reliability of our internal and external tools Process Automation : Designing intelligent workflows that eliminate bottlenecks and allow our experts to focus on the most technical aspects of the Snowflake platform Incident discovery: using embeddings, LLMs, clustering, and agents to detect potential widespread issues more quickly Now, the team is growing, and we are looking for a Software Engineer to join us. In this role, you will work closely with the state of the art LLM models, fine-tune them, develop agents, apply various clusterings, summarizations, embeddings, and so on. Ev

HackerRank helps companies like NVIDIA, Amazon, and Microsoft hire and upskill the next generation of developers based on skills, not pedigree. Our platform is trusted by over 2,500 of the world’s most innovative companies to build strong engineering teams ready for what’s next. Software has entered an era where humans and AI build side by side. As this shift accelerates, the definition of strong technical talent is changing. We give companies better ways to identify and invest in next-generation skills. People at HackerRank care deeply about the impact of their work and sweat the small details so our customers can be wildly successful with products they genuinely love to use. We move with urgency and believe great outcomes come from high standards. About the role We are looking for a Senior AI Data Operations Manager to own and run our end-to-end LLM model data creation pipeline from sourcing and managing vendors, to coordinating with engineering teams to evaluate model performance to closing the loop by creating targeted data for edge cases ensuring the data our models train on meets the highest quality standards. This role will manage the end-to-end AI data pipeline across 10+ AI features spanning multiple products on our platform This is a cross-functional operations role that sits at the intersection of ML, product, and operations management. You will be the connective tissue between our machine learning engineers, internal annotators, and external vendors, translating technical requirements into actionable data creation workflows and ensuring every batch of data that reaches our models is accurate, well-annotated, and fit for purpose. Critically, you will also drive automation across the pipeline, designing and deploying AI agents that eliminate manual bottlenecks and make the entire operation smarter over time. What you will do Own the full AI feature development lifecycle, from sourcing data to quality management and relationship building at scale. Design an

About Clutch Clutch is Canada’s largest online used car retailer, delivering a seamless, hassle-free car buying and selling experience. Customers can sell their car instantly online using our ML-driven pricing model, or browse thousands of cars to buy, all from the comfort of their home. Named three years in a row to the Globe & Mail’s list of the Top Growing Companies in Canada and awarded spots on Deloitte’s Technology Fast 50™ and Fast 500™ lists, we’re looking to add curious, hard-working, and driven individuals to our growing team. Headquartered in Toronto, Clutch was founded in 2017 and is backed by world-class investors including Canaan, BrandProject, Real Ventures, D1 Capital, and Upper90. About the team Product & Design is Clutch’s creative engine. We solve some of the hardest problems in the business: improving the customer experience, building internal tools that power our operations, running growth experiments, connecting systems and data, and finding better ways to buy, sell, and move cars. The way we build products has changed significantly. Using Ignition, our platform for agentic engineering, individuals can now work across parts of the product-development process that traditionally required several specialized roles. A project that once involved a large team for months can increasingly be owned by one or two people and shipped in days. We call those people builders . A builder can move from understanding a business problem to shaping a solution, designing the experience, building it, testing it against realistic data, putting it in front of users, and iterating based on what they learn. This role is for someone excited by the fact that the boundaries between product, design, and engineering are becoming increasingly blurry. What you’ll do Own important product problems end-to-end, from understanding the business and user problem through building and shipping the solution Immerse yourself in Clutch’s operations, customers, systems, proc

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

About the Role Datadog’s Technology Partnerships team builds and scales partnerships with the technology companies that matter most to our customers from AI/ML platforms to data platform providers. As a Technology Partner Manager, you will own the full, 360-degree relationship with a portfolio of strategic Technology Partners, with a particular focus on cutting-edge AI/ML and Data Platform companies. You’ll be the connective tissue across three pillars of partnership: co-build (joint product and integration roadmaps), co-market (joint awareness and demand generation), and co-sell (joint pipeline and revenue). This is a highly cross-functional, relationship-driven role that requires equal comfort in a product roadmap discussion, a marketing planning session, and a sales enablement meeting. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do 360° Relationship Ownership: Own the end-to-end partner relationship for a portfolio of AI/ML and Data Platform technology partners, serving as the primary point of contact and trusted advisor across product, engineering, marketing, and sales stakeholders on both sides. Co-Build: Partner closely with Datadog Product and Engineering teams to identify, prioritize, and drive joint integration roadmaps; ensure integrations are built, launched, and continuously improved to meet customer needs. Co-Market: Design and execute joint marketing programs including webinars, blog posts, customer case studies, launch campaigns, and event collaboration with Datadog product marketing and partner marketing teams to build awareness and demand for joint solutions. Co-Sell: Build and execute go-to-market and co-sell plans with Datadog channel team, partner field and sales teams; enable Datadog’s global sales organization and partner sellers o

Technology Partnerships Team at Datadog About the Role Datadog’s Technology Partnerships team builds and scales partnerships with the technology companies that matter most to our customers from AI/ML platforms to data platform providers. As a Technology Partner Engineer, you will be the technical bridge between Datadog and our partner developer community, acting as a consultant who helps partners build world-class monitoring solutions on the Datadog platform. You will be the primary technical contact for our partners, guiding them through the entire integration lifecycle from initial architectural design to final product integrations, and launching on the Datadog Marketplace. This is a unique role that combines deep technical troubleshooting with high-level consulting and platform advocacy, working directly with external developers and seeing your contributions immediately reflected in the Datadog ecosystem. What You’ll Do Technical Advisory: Act as the technical lead for partners, advising on OAuth flows, log pipelines, OpenTelemetry, and MCP-based and API-based integrations and configurations. Co-Build: Partner closely with Datadog Partner, Product and Engineering teams to identify, prioritize, and drive joint integration roadmaps; ensure integrations are built, launched, and continuously improved to meet customer needs. Architectural & Code Review: Perform architectural assessments and deep-dive code reviews for partner integrations and marketplace repositories, ensuring they meet Datadog’s quality rubric. Technical Troubleshooting: Solve complex technical challenges for partners via dedicated technical consultations. Platform Advocacy: Identify friction points in the Datadog platform and partner with internal Product and Engineering teams to build a better developer experience. Documentation & Tracking: Maintain public-facing developer documentation including blog posts, and internal tracking systems to ensure transparency and scale. Market Awarenes

About the role Chime’s Machine Learning Platform (MLP) team builds and operates the infrastructure, tooling, and developer experience that powers machine learning across the company. We enable data scientists and ML engineers to develop, train, deploy, and monitor models reliably and efficiently. As a Senior Software Engineer on the Machine Learning Platform team, you will design and build scalable systems spanning traditional machine learning and emerging AI workloads, including model training, feature computation, real-time inference, foundation-model access, evaluation, and agentic orchestration. You’ll work at the intersection of distributed systems, cloud infrastructure, applied machine learning, and AI product engineering. This role focuses on creating secure, reliable, and reusable platform capabilities that help teams choose the right approach, from conventional predictive models to LLM-powered and multi-step agentic systems, while maintaining strong standards for evaluation, observability, governance, privacy, and cost efficiency. In this role, you can expect to Design, build, and operate scalable ML and AI infrastructure on AWS. Design and operate shared platform capabilities for LLM and agentic workloads, including model access, prompt and configuration lifecycle, retrieval, tool integration, state management, and workflow orchestration. Build evaluation frameworks for non-deterministic AI systems, including offline benchmarks, regression testing, online quality signals, human feedback, and failure analysis. Establish observability, reliability, and governance for models and agents, covering traces, model and prompt versions, tool calls, latency, token usage, quality, safety, privacy, and cost. Help teams make principled architecture decisions across traditional ML, LLM-powered applications, and agentic workflows, and contribute to the platform’s technical roadmap. Build distributed training, batch inference, and large-scale processing systems using

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Team The Perception ML Operations team sits at the center of how Nuro's vehicles learn to see. We are responsible for the training and evaluation data that powers perception models across every sensor modality: vision, lidar, radar, and beyond. We work alongside ML engineers, product owners, data engineers, and external labeling partners to turn ambiguous, fast-moving requirements into data deliverables the Perception team can build on with confidence. This is a team that operates at the intersection of ML urgency and operational discipline. Here is what the work actually looks like day-to-day: Sitting in a roadmap review, hearing a new feature requirement land, and walking out with a concrete data collection and labeling plan already scoped against timeline and budget. Reviewing vendor throughput against milestone dates and catching a capacity gap before it would become a release risk. Querying pipeline data directly to unders

CSQ427R228 As a Senior Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy. The impact you will have: Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. Work with the Data

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 the role: As a Senior Product Manager, Clinician Experience you can expect to ship into production at major health systems, work at the AI frontier with real clinical constraints, and operate cross-functionally with engineering, ML, clinical, design, and partner-facing teams. What you will do: Clinician Experience You'll own the products clinicians use to review, act on, and trust what our AI produces: the tools that surface AI-gathered patient context, support clinical decision-making, and fit into workflows that are already overloaded. The clinician-facing product surface: intake summaries, AI-generated patient context, review/override workflows, and documentation support tooling The end-to-end encounter workflow, from AI-gathered context through clinical decision to documentation. Trust and explainability mechanics — how the AI surfaces its reasoning and how clinicians correct or override it Reduction of clinical workload: minutes saved per encounter, clicks removed, documentation burden reduced Work directly with practicing physicians (internal and health system partners) to validate that designed workflows reflect real clinical behavior Partner with clinical leadership on safety review and escalation protocol Engineering and AI/ML teams to translate clinical trust requirements into verifiable, implementable product behavior What we’re looking for: 4+ years of product management experience shipping consumer or B2B2C software; at least one product you owned end-to-end from ambiguity to launch Experience with AI/ML-powered products — you understand non-determinism, know why evals matter, and can reason about model behavior as a product surface Strong analytical fluency: you can pull your own data, define your own metrics, and won't wait for an analyst to tell you what's happening Exceptional written communication — your docs create alignment instead of requiring meetings to explain them Comfort operating in regulated, high-stakes environments Client-facing e

About the position Showpad is building a Revenue Intelligence engine that transforms raw signals—CRM data, email threads, transcripts, and content engagement—into prescriptive AI guidance. We are looking for a technical Product Manager to own the unified data intelligence layer that powers this engine. You will define how we capture and model data, and critically, determine the best retrieval and inference strategies (Search, RAG, Knowledge Graphs, or Vector Similarity) for every use case. Key Responsibilities Data Modeling & Architecture : Define the canonical model for entities (deals, contacts, skills) and establish the retrieval strategy—choosing between keyword, dense vector, hybrid, or graph traversal based on latency and accuracy. Search & RAG Ownership : Own the end-to-end RAG pipeline (chunking, embeddings, indexing). Write technical specs for retrieval layers in Meeting Prep and Roleplay AI, and define evaluation metrics (Recall@k, MRR). Revenue Intelligence Roadmap : Drive the vision from "trusted foundation" to "prescriptive AI." Own the product logic for Deal Health and Winning Behavior models. Platform Enablement : Act as the internal PM champion for the data platform, providing semantic primitives, event taxonomies, and data contracts to other product squads. Discovery & Strategy : Conduct deep customer discovery and stay ahead of LLM/Search trends, translating fuzzy business questions into scoped ML problems. Required Skills Must haves 5+ years in PM: at least 2 years specifically owning data platforms, search, analytics, or ML products. Retrieval Expertise: Hands-on experience shipping RAG pipelines or search systems. You understand the trade-offs between BM25, vector search, and reranking. Data Technicality : Fluency with Datalake architectures (Delta Lake, BigQuery, etc.) and strong entity-relationship modeling skills. ML Fluency : Ability to define features, label designs, and evaluation metrics. You can review a technic

We're looking for a Senior Machine Learning Engineer with strong computer vision expertise to join our Biometrics team. You'll ramp up on the biometrics domain while contributing to the design, training, and scaling of our ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Design and develop computer vision models and pipelines, contributing to biometrics use cases such as face detection, quality assessment, and recognition Collaborate on benchmarking of models across datasets and operating conditions Train and optimize models using PyTorch, TensorFlow, and/or JAX Contribute to end-to-end ML pipelines, from data ingestion to deployment. Help design automated pipelines (Airflow) for data ingestion and cleaning. Production Engineering: Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and support deployment on AWS. Collaborate with and mentor ML engineers, and contribute to technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning with a focus on Computer Vision (e.g., image classification, object detection, segmentation, image quality, generative models) Strong Computer Vision fundamentals Fairness & Ethics: Awareness of algorithmic bias and willingness to learn domain-specific fairness practices Strong Engineering: Strong proficiency in Python (Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code Systems Architecture: Experience designing or contributing to ML pipelines and familiarity with orchestration tools like Airflow Cloud Native: Experience with GPU-based training and deploying ML services on AWS Nice to Have Research Publications in top computer vision venues (CVPR, ICCV, ECCV) Large Scale Search: Familiarity with vector databases and ANN search Synthetic Data: Experience with GANs or diffusion models for data augmentation Mobile

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective. You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. You Will: Model and Pipeline Automation Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models. Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models. Governance & Compliance Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards. Performance Monitoring Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. Incorporate user feedback for iterative improvements and manage necessary model retraining cycles. Cross-Functional Collaboration Act as the "glue" between Data Scientists (who build models

About Outreach Outreach, founded in 2014, is the only complete agentic AI platform for revenue teams. Outreach infuses agentic AI, conversation intelligence, and assistive AI to power hundreds of use cases across revenue motions. From new logo prospecting to expansions, deal acceleration, driving retention, and forecasting, Outreach AI automates workflows and frees sellers to focus on more strategic conversations and actions. Revenue leaders benefit from connected account visibility, performance insights, and higher forecasting accuracy across every GTM team. World leading enterprise organizations use Outreach to power their revenue teams, including Databricks, SAP, Siemens, and Verizon to name a few. About the Team The Dialog Understanding and Generation team is building the industry's most advanced agentic AI capabilities for revenue orchestration, the end-to-end coordination and execution of sales and customer engagement workflows. Our mission is to transform raw customer interactions and CRM data into structured intelligence that powers the entire revenue lifecycle. We operate at the intersection of machine learning, LLM-powered systems, and cloud-scale engineering, driving both current and next-generation AI initiatives at Outreach. We are a team of applied data scientists who thrive on solving complex scientific and engineering challenges. The work is roughly an even split between applied ML research and production engineering, so you should be excited about both. You'll collaborate closely with exceptional engineers and product managers in a fast-moving, high-impact environment, applying your creativity and expertise to build innovative solutions that push the boundaries of agentic AI. Your Daily Adventures Will Include: <li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="5" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":