Senior Ml Science Manager Jobs

SPECIFIC JOB RESPONSIBILITIES Pipeline Management: Maintain high-throughput streaming pipelines to ingest logs from various sources (Firewalls, Cloud, Endpoints) to a central destination. Log Normalization: Write parsers to convert raw, messy logs into standard schemas (e.g., OCSF or ECS) for consistent querying. Cost Optimization: Implement routing logic to send "high-value" data to the SIEM and "bulk" data to low-cost Object Storage (Data Lake). Data Preparation: Clean and structure data to enable AI/ML detection models and advanced analytics. EXPERIENCE REQUIRED Data Engineering: Proficiency in Python (for ETL) and SQL (for complex querying). Streaming Tech: Experience with Message Queues (e.g., Kafka, Pub/Sub) and stream processing concepts. Log Handling: Mastery of Regex and log parsing strategies for standard formats (Syslog, CEF, JSON). Storage Architecture: Understanding of Data Lake principles (Parquet/Avro formats) vs. Data Warehouses. QUALIFICATIONS, SKILLS, & KNOWLEDGE Experience with Vector Databases for storing embeddings. Knowledge of Log Observability/Routing tools (middleware that routes logs). Familiarity with Big Data frameworks (e.g., Spark, Flink). PROFESSIONAL DEVELOPMENT EXPECTATIONS Ability to embrace Clearwater's CLEAR core values (Commitment to Client Success, Lead with Accountability, Integrity & Collaboration, Excellence in All That We Do, Advance Colleague Success, Respect & Transparency) and culture. The base salary range for this role is 35,000- 45,000]. Base salary is part of our total rewards package which also includes the opportunity for merit-based salary increases, eligibility for our 401(k) plan, medical, dental, vision, life and disability insurances and leaves provided in line with your work state. Our robust time-off policy includes flexible paid time off, 11 paid holidays, and paid sick time. Total compensation, including base salary to be offered, will depend on elem

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As Senior Technical Program Manager for the Human-in-the-Loop (HITL) Operations , you will own the end-to-end lifecycle of Roblox's AI data labeling and model evaluation ecosystem. This is a high-leverage, high-ownership role at the intersection of Research, Engineering, and Operations. You will scale our data operations that is handling million of items evaluated annually today with projection of 4x the current volume by 2030, managing a multi-million annual budget and a distributed workforce of 100+ remote contractors — all while driving the platform evolution from manual workflows to AI-assisted, LLM-accelerated operations. This is a rare opportunity to build the data infrastructure that directly determines the quality of Roblox's AI models across creator tools, content discovery, in-experience AI, and 3D generative content — at the exact moment when human judgment is the critical ingredient for getting these models right. You Will Lead data programs end-to-end. Own the full lifecycle of labeling and model evaluation workflows across Roblox's AI teams — from translating ambiguous ML requirements into structured annotation tasks, to overseeing contractor execution, quality review, a

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The vision for the Batch Infra team @ Affirm team is to provide reliable, scalable, self-serve and Affirm-optimized compute solution to enable ML, Product, and Financial Engineering success. Our team is responsible for building and maintaining compute platform that serves as a backbone for processing various Business critical batch workloads at Affirm through a wide suite of scheduled and on-demand compute solutions built on the cloud. Affirm is growing rapidly and so is the need for reliable and high availability frameworks. If solving infrastructure challenges at scale excites you, come join us! What you’ll do You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will proactively identify project, process, technology or business issues, advocate for them, and lead in solving them. You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts. You will foster a culture of quality and ownership on your team by setting or improving code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. You will help develop talent on your team by providing feedback and guidance, and leading by example. What We Look For: You have 4+ years of experience desig

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The vision for the Batch Infra team @ Affirm team is to provide reliable, scalable, self-serve and Affirm-optimized compute solution to enable ML, Product, and Financial Engineering success. Our team is responsible for building and maintaining compute platform that serves as a backbone for processing various Business critical batch workloads at Affirm through a wide suite of scheduled and on-demand compute solutions built on the cloud. Affirm is growing rapidly and so is the need for reliable and high availability frameworks. If solving infrastructure challenges at scale excites you, come join us! What you’ll do You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will proactively identify project, process, technology or business issues, advocate for them, and lead in solving them. You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts. You will foster a culture of quality and ownership on your team by setting or improving code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. You will help develop talent on your team by providing feedback and guidance, and leading by example. What We Look For: You have 4+ years of experience desig

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world's most important decisions. Scale's evaluation and data products shape how the industry trains and measures frontier models. Our benchmarks and leaderboards influence model development and purchasing decisions across the AI ecosystem, and our data and environments help leading labs build what comes next. These roles are deeply cross-functional. You will work across AI Product Management, ML Research, Engineering, Operations, and Go-To-Market teams, and directly with frontier AI labs and enterprise customers, representing Scale as a thought leader in how models are trained and measured. Whichever portfolio you own, you will own it end-to-end: strategy, roadmap, infrastructure, governance, customer adoption, and business impact. PMs here operate with significant autonomy, ship frequently, and are expected to be deeply analytical and hands-on. The ideal candidate combines strong product judgment, technical fluency, operational rigor, and customer-facing experience, with a passion for turning emerging model capabilities into scalable products. Open Roles Senior AI PM, Coding: Own Scale's Coding portfolio, built on SWE-Bench Pro (which cut frontier scores from 70%+ to roughly 23%), SWE Atlas, and our FrontierBench contributions. You'll decide what comes next as agents saturate current tasks, and turn that benchmark credibility into revenue from SFT and preference data, RL environments, and agentic coding evals. You'll also own the coding infrastructure roadmap and our expert network of professional software engineers. This role requires hands-on software engineering depth. Senior AI PM, Leaderboards: Own and scale the SEAL Leaderboard portfolio across all of Scale's domains, turning cutting-edge evals into truste

Senior Director, #1080 Leadership in federal technology environments · AI enabled software development · Application modernization · Mission focused solutions Location: Reston, VA Clearance: U.S. Citizenship is required. Must possess or be able to obtain and maintain a DHS Public Trust clearance. A Role with Purpose and Impact Dev Technology Group is seeking a Senior Director to lead a portfolio of federal software development and modernization programs supporting critical customer missions. Dev Technology applies cloud development, AI/ML, DevSecOps, data analytics, cybersecurity, and other modern technologies to help federal agencies solve complex challenges and advance their missions. The Senior Director will provide strategic leadership, customer engagement, operational oversight, and people leadership needed to ensure the continued success and growth of this portfolio. In addition to maintaining a deep understanding and appreciation of the missions of our federal government customers, the Sr. Director will also have a strong command of the environment in which they operate. This includes remaining informed about cloud technologies, emerging technology trends, modern software delivery practices, artificial intelligence, cybersecurity, and the evolving federal technology landscape. Who Thrives Here The successful candidate is a strategic and client-focused technology leader who can move comfortably between executive customer conversations, solution and modernization strategy, and the leadership of experienced Project Managers. This leader is growth oriented and works cross-functionally with internal and external stakeholders and engages technical teams to identify opportunities to better support the customer mission, shape and advance solutions, and drive continued innovation. This opportunity is well suited for someone who: Builds trusted, long-term relationships with federal customers by understanding

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. Build the future of data. Join the Snowflake team. The Snowflake Machine Learning Platform team’s mission is to enable customers to bring their machine learning and deep learning workloads to Snowflake. Our customers want to build powerful models with the ever-increasing data in Snowflake but face several challenges including infrastructure optimizations, orchestration, performance, and security. The team aims to solve these challenges by building highly integrated platform solutions that are simple, secure, and enable end-to-end ML workflows. We are on an early journey to build the most scalable machine learning and data platform without sacrificing the benefits of a single platform and governance. We are looking for outstanding technical leaders who will join our ML Platform team to build the next-generation platform and play a pivotal role in this journey by understanding Snowflake’s core platform architecture and evolving it to enable state-of-the-art machine learning and LLM workloads. Join us to define strategies, set technical directions, design and execute, engage and deliver innovation, and unlock the power of AI for thousands of enterprise customers. This position is based in Menlo Park, CA, and Bellevue, WA. RESPONSIBILITIES : Help define and own the roadmap, wor

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. On the ML Fraud team, you’ll build and improve machine learning systems that make real-time transaction decisions, protecting consumers and merchants while balancing fraud loss, customer experience, and conversion. You’ll work closely with experienced ML engineers, platform partners, and cross-functional stakeholders to take models from idea to prototype to production, and to keep them healthy with strong measurement and monitoring as fraud patterns evolve. What you’ll do - You will lead development of new fraud prediction models using a mix of approaches for tabular, graph, and behavioral data - You will build and scale feature pipelines and training datasets from proprietary and third-party signals, partnering with data and platform teams when needed. - You will prototype new modeling ideas and features, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls. - You productionize models: integrate into batch and/or real-time decision systems, and improve reliability, latency, and operational robustness. - You will instrument and monitor model and data health, and help define retraining/backtesting workflows as fraud patterns evolve. - Identify and implement foundational improvements to how the team builds models. - You will collaborate across Engineering, Fraud Analytics, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non-technical audiences. What we look for - You have 6+ years experience researching, training, tuning and launching ML models at scale. Relevant PhD can count for up to 2 years of experience. - Track record of delivering high impact machine learning models in a low latency live setting - Strong Python skil

About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Senior Software Engineer on Spark Platform, you will set the technical direction for our in-house Spark deployment and shape the architecture that will run DoorDash's data, analytics, and ML compute for the next five years and beyond. You will own the deep, cross-cutting problems that span the runtime, the shuffle service, the scheduler, and the overall service reliability — making the architectural calls that compound across the platform's lifetime. You will partner with the Engineering Manager on technical roadmap, hiring, and team shape, and act as the senior technical voice in cross-team partnerships with Data Engineering, ML Platform, and product engineering teams that depend on the platform. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Set the multi-year technical direction for an in-house Spark-on-Kubernetes platform — runtime, shuffle, scheduler, reliability — and make the architectural calls that compound for years. Own the deepest distributed-systems problems on the team: shuffle architecture, multi-tenant scheduling, runtime performance, and the failure modes that only show up at scale. Partner with the Engineering Manager on technical roadmap, hiring, inte

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Host Pricing & Settings team builds the platform and tools that help hosts run their business — with pricing strategies informed by market intelligence, comparable listings, and demand signals. We partner with Search, Listings, Tax, and Payments to ensure our guidance is accurate, timely, and trusted. Behind every pricing recommendation is a sophisticated ML system undergoing a fundamental rearchitecture. Our north star: a serving infrastructure where training, inference, and evaluation are consistent by design — features from a centralized store, model composition in one place, and backfills available on demand so data scientists and MLEs can evaluate candidates in days, not weeks. The Difference You Will Make: As a senior technical individual contributor, you will own the technical strategy for the full Modeling → ML Serving → API interface across the Host Pricing org. Although you will be at one of our highest levels of seniority, all individual contributors at Airbnb are Software Engineers — you are expected to be hands-on and contribute code. Define the architecture and contracts governing how models move from development to production — feature store design, model schema management, online/offline inference consistency, and multi-version support. Lead the buildout of a unified serving stack that eliminates per-model one-off implementations and gives data scientists a turnkey path from training to production. Architect backfill and evaluation infrastructure so the modeling team can simulate production inference over historical data in days, not weeks. Establish do

The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence. As a Machine Learning and System Optimization Engineer, you will orchestrate and allocate overall system capacity to various core perception models running on-bot, as well as drive large initiatives that allow for more efficient inference by sharing various parts of the perception stack with one another. You will focus on bringing highly efficient, production-ready large-scale models to our on-vehicle stack. We are looking for experts with hands-on experience compressing, accelerating, and deploying complex models, including LLMs, VLMs, or foundation models, for power- and thermal-constrained vehicle SoCs. In addition, you will optimize ML models, write custom CUDA kernels, and build highly concurrent inference code to ensure real-time, deterministic execution on edge devices. In this role, you will: Allocate and distribute system resources (CPU/GPU/interconnect) to various models and inference engines running on the robot. Spearhead cross-cutting initiatives that allow for better compute utilization through sharing/fusing models and better scheduling strategies. Optimize large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs) using advanced quantization (PTQ, QAT), pruning, mixed-precision inference frameworks, and parameter-efficient fine-tuning (LoRA, QLoRA). Architect and implement model conversion and compilation pipelines using TensorRT for edge deployment. Write production-level, low-latency, and memory-safe C++ and CUDA code for real-time inference on vehicle systems. Qualifications: Deep experience in system and performance optimization in CPU/GPU systems designed for low latency or high throughput. Deep expertise in working with real-time systems & required

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

Location Details: India, Remote At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join Our Team... Here at GoDaddy, the ML Engineering (MLE) team exists as the backbone of our machine learning infrastructure, enabling ML scientists and product teams across Domains to ship models to production reliably, efficiently, and at scale. This team owns the full lifecycle of ML systems — from CI/CD pipelines and model serving infrastructure to GPU workload orchestration and observability. Through disciplined engineering practices, thoughtful system design, and close collaboration with ML scientists, data engineers, and product teams, we deliver the platform that powers domain search, pricing, recommendations, and emerging AI experiences for millions of customers worldwide. We are currently looking for an experienced, highly motivated Senior Engineering Manager to lead our ML Engineering team based in India. This is an established team with existing engineers — we expect the candidate to ramp up quickly on our ML infrastructure stack, build strong relationships with the team, and partner with both India-based teams and US-based teams to drive execution and grow the team further. This individual will join us on our journey to build and scale ML infrastructure that serves real-time predictions at low latency, automates model deployment and promotion, and provides the observability and reliability guarantees that production ML systems demand. Become part of a team that bridges the gap between ML research and production engineering — shipping systems that directly impact GoDaddy's core revenue. What you'll get to do... Lead a team o

About the Team & Role: We're building SAGE , Rubrik's Semantic AI Governance Engine, which is the first system designed to monitor, govern, and remediate autonomous AI agents in real time. SAGE powers Rubrik Agent Cloud: enterprises define governance policies in natural language, and SAGE's custom small language models act as judges on every agent action. These models are fast enough to sit in the live request path and accurate enough that customers trust them with allow/block decisions on production traffic. At its core, SAGE is "LLM-as-judge" applied to AI governance, utilizing the same technique most teams use for offline evaluation but productionized for real-time enforcement at enterprise scale. Our first-generation SLM Policy Guard already outperforms the larger frontier models we've benchmarked against on accuracy while running approximately 5x faster on the same workload. We're hiring to push that lead even further. As an Applied ML Engineer on the SAGE team, you'll work end-to-end across the model lifecycle: curating data, training small models, serving them at production latency, and closing the feedback loop with real customer signals. The models you build don't just enforce policies in the live request path; they will also drive Agent Rewind, Rubrik's capability to instantly and precisely undo destructive autonomous-agent actions and restore the affected data to a trusted state. We're a collaborative, applied team that ships models to enterprise customers within weeks, and we're passionate about proving that small, specialized models can outperform frontier LLMs at the problems that matter most for AI safety and governance. Nature of the Specialized Duties ➢ Training, Fine-Tuning, and Distilling Production Small Language Models and Classifiers (25% of time) Owning the full training lifecycle for the SLMs and classifiers in SAGE's real-time enforcement path, including base-model selection, supervised fine-tuning, preference optimization (DPO/RLA

About the Team The Ads & Promos Delivery team powers the last-mile delivery of ads and promotions, two marketing products offered to merchants, connecting merchant intent with consumer demand across search and discovery experiences. As a Senior Staff Engineer, you will lead the technical direction for AI-first experiences, including ranking and relevance systems that sit at the core of our ads marketplace and shape how ads are selected, ordered, and personalized in real time across all verticals. You will design and build next-generation AI-first ranking systems using state-of-the-art techniques such as sequence modeling, deep learning, and large language models (LLMs). Your work will span query understanding, user and merchant representation learning, contextual relevance, and multi-objective optimization, balancing advertiser value, consumer experience, and marketplace health at scale. You will set the long-term technical vision, drive cross-team alignment, and translate cutting-edge research into production systems that operate under strict latency, scale, and reliability constraints. As DoorDash expands into 40+ global markets and new verticals such as Grocery and Retail, this role offers a rare opportunity to define how modern AI, including sequential models and LLM-powered decisioning, reshapes ads relevance in a closed-loop marketplace. About the Role Apply state-of-the-art machine learning and LLM techniques to problems across personalization, query understanding, user and content understanding. Rigorously evaluate ML and LLM models using a combination of offline analysis and online experimentation, designing metrics and experiments that clearly measure quality, impact, and tradeoffs. Own the full model lifecycle from research to production, including data analysis, model development, evaluation, offline and online A/B testing, and continuous iteration. Partner closely with product managers, data scientists, and designers to ensure AI-driven systems deli