Senior Ai Ml Architect Jobs

Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Senior or Lead Bioinformatics Scientist to join the team building the technology at the heart of that effort. You will work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. You will help advance the state-of-the-art and drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients. PRIMARY RESPONSIBILITIES: Develop and validate new algorithms to analyze large multimodal epigenomic datasets Drive research analyses through implementation, testing and performance evaluation, including developing new features within existing pipelines Work with sequencing and clinical data from large cohorts, ensuring data integrity and quality control Partner with molecular biologists and clinical scientists to solve challenging, open-ended problems Visualize results and present complex findings to both technical and non-technical audiences Contribute to the team’s standards for code quality and reproducibility QUALIFICATIONS: Ph.D. in Bioinformatics, Computer Science, Biology, or a related field; alternatively a Bachelor’s or Master’s degree with at least 4 years of professional experience Track record developing and validating analysis workflows for high-throughput sequencing data Experience applying and evaluating statistical and ML methods to large datasets Strong quantitative reasoning and data analysis skills, applied effectively to real scientific problems. Software development experience, including proficiency in Python and its scientific computing ecosystem Fluent using Linux command-line tools and cloud computing environments Strong verbal and written communication skills Preferred Experience Working knowledge of DNA methylation and other epigenomic data Experience with cell-free DNA and liquid biopsy samples Ba

Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Senior or Lead Bioinformatics Scientist to join the team building the technology at the heart of that effort. You will work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. You will help advance the state-of-the-art and drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients. PRIMARY RESPONSIBILITIES: Develop and validate new algorithms to analyze large multimodal epigenomic datasets Drive research analyses through implementation, testing and performance evaluation, including developing new features within existing pipelines Work with sequencing and clinical data from large cohorts, ensuring data integrity and quality control Partner with molecular biologists and clinical scientists to solve challenging, open-ended problems Visualize results and present complex findings to both technical and non-technical audiences Contribute to the team’s standards for code quality and reproducibility QUALIFICATIONS: Ph.D. in Bioinformatics, Computer Science, Biology, or a related field; alternatively a Bachelor’s or Master’s degree with at least 4 years of professional experience Track record developing and validating analysis workflows for high-throughput sequencing data Experience applying and evaluating statistical and ML methods to large datasets Strong quantitative reasoning and data analysis skills, applied effectively to real scientific problems. Software development experience, including proficiency in Python and its scientific computing ecosystem Fluent using Linux command-line tools and cloud computing environments Strong verbal and written communication skills Preferred Experience Working knowledge of DNA methylation and other epigenomic data Experience with cell-free DNA and liquid biopsy samp

Fanatics Commerce is the global leader in licensed sports merchandise, operating a vertically integrated platform that designs, manufactures, and delivers officially licensed apparel, jerseys, headwear, and collectibles for major leagues, teams, and events worldwide. With more than 900 e-commerce sites and a global omnichannel presence across digital, in-venue, and retail, Fanatics Commerce reaches fans in over 180 countries and powers official fan experiences for many of the world's most iconic sports properties. At Fanatics, we bring our BOLD Leadership Principles to life every day - building championship teams, obsessing over fans, acting with entrepreneurial speed, and delivering with a determined and relentless mindset. As we continue to scale our global platform, the Senior Data Scientist, Supply Chain & Inventory Optimization will play a critical role in maximizing supply chain efficiency and inventory financial performance through ML-driven modeling, pricing optimization, and demand forecasting. ROLE OVERVIEW This role sits within a high-impact team responsible for product lifecycle modeling, pricing and promotional optimization, clearance management, demand forecasting, network simulation, and inventory sourcing, allocation, and balancing. The Senior Data Scientist will bring a rigorous, ML-driven mindset across operational modeling, forecasting, pricing, and product strategy — moving fluidly across domains in a collaborative, fast-moving team culture with a strong emphasis on delivering measurable business impact amid frequently shifting requirements. The Senior Data Scientist delivers business and fan impact through BOLD leadership and execution excellence, leveraging data, automation, and AI-enabled insights. HOW WILL YOU DRIVE IMPACT Success is measured by the ability to deliver results through BOLD capabilities and measurable outcomes. Team & Leadership Impact (Build Championship Teams) Partner cross-functionally with engineering, product, and

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

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 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":

#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors As Data Scientists at Nextdoor, you will have the opportunity to influence strategic decisions with product analytics, drive better experimentation and build online and offline ML solutions. We use a semi-embedded team structure, with data team members interfacing directly with product and engineering stakeholders. The Data Science group is made up of people from a diverse set of backgrounds and perspectives, trained in fields as wide-ranging as economics, psychology, geography, physics, statistics, and operations research. We are the mathematical decision scientists for the product development organization and play a proactive and collaborative role in building and improving the product. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make As a Senior Data Scientist on the Search team, you will shape how neighbors find the people, places, posts, and business

Role Overview You are a senior product leader who wants to shape how AI transforms IT and cyber risk management at scale. In this role, you will own one of the most strategic product areas in a global GRC SaaS platform, defining how organisations identify, assess, and act on cyber risk — and how CISOs and boards get the clarity they need when it matters most. You will set and drive the product vision, roadmap, and outcomes for IT & Cyber Risk on a multi-solution platform used by enterprises worldwide. You will partner closely with engineering, design, data science, and senior leaders to build AI-native capabilities that automate risk detection, prioritisation, and reporting. Your work will have high executive visibility, real strategic weight, and direct impact on how customers manage governance, risk, and compliance. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the end-to-end product strategy and roadmap for IT & Cyber Risk, aligning to company objectives and broader platform direction. Design and deliver AI-powered features (LLMs, agents, ML models) that automate risk identification, assessment, and reporting for enterprise security and risk teams. Partner with engineering, data science, and design to define technical approaches, ship high-quality releases across web, mobile, and API, and iterate using product analytics. Develop deep market and customer insight by engaging regularly with CISOs, security leaders, and risk managers, and turn those insights into clear product bets. Define, track, and communicate product KPIs, AI performance metrics, and north star outcomes to senior stakeholders, including business cases for major investments. Work cross-functionally with Sales, Customer Success, Professional Services, and Marketing to ensure successful launches and adoption of new IT & Cyber Risk capabilities. These are the essentials you’ll need to get an interview 7+ years of product management experience, includi

About Appier Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. Open to overseas candidates/Visa Support This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan. The Impact You’ll Make at Appier Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team , which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery. In this role, you’ll further improve bidding strategies, audience targeting and creative optimization by deep-diving RTB ecosystem including SSP/DSP/MMP to design the strategy, enhancing user signals or applying advanced deep learning model What You’ll Work On Deep-dive the RTB ecosystem to identify the potential direction and decide the bidding strategy Leverage advance deep learning model to improve bidding/audience model performance Co-work with teams to improve real-time/long-term user interaction signal collection and to further improve model performance What We’re Looking For Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, or related field. 3+ years of industry experience on RTB ecosystem Proficiency in Python and SQL experience with modern ML frameworks and deep learning model (PyTorch, TensorFlow, etc.). Strong ownershi

Who We Are Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale, empowering a safer, richer, and more connected future. About the Role The Mapping team in Nuro takes a machine learning-first path to unblock geographic capability with lower costs. This team plays a crucial role in the advancement of autonomous driving systems by creating and improving different components in the full lifecycle of ML models for multiple teams in this organization. We are searching for an engineer with experience building reliable and scalable machine learning infrastructure and a strong desire to contribute to the future of robot navigation for logistics and transportation. About the Work Mainly focus on building and improving HD map generation and release pipelines. Develop scalable workflows to manage first party and third party map data. Develop and manage APIs for internal users to access data. Improve and refactor existing workflows and toolings to boost efficiency. Engage with other mapping teams to help identify issues and establish long-term relationships that include knowledge sharing. About You BS in Computer Science, Robotics or another quantitative area. You have experience in one or more of the following areas: large-scale distributed systems; data storage and processing systems; advanced algorithms using C++ and Python; multithreading; and software performance tuning and optimization. Ability to efficiently develop, debug, and support new technologies in a changing environment. Str

About Appier Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. The Impact You’ll Make at Appier Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team , which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery. In this role, you’ll build identify graph to enrich unified customer profile and also identify high purchase value users to drive ROAS by machine learning model. What You’ll Work On Leverage scientific methods to build identify graph and identify high-value users Drive online experiments to continuously improve ROAS Own the project independently. Partner with product stakeholder, backend and frontend to provide measurement solution for our customers. What We’re Looking For Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, or related field. 3+ years of industry experience on identify graph, ID mapping and cross-device mapping in digital Ads related fields, and generate mapping and profile under large-scale data. Proficiency in Python and SQL experience with modern ML frameworks (PyTorch, TensorFlow, etc.). Strong ownership and collaboration skills. #LI-AK1

About Appier Appier is a software-as-a-service (SaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. About the Role We are looking for a Machine Learning Scientist (LLM & Agents) to join the Enterprise Solution Science Team. This team focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data. In this role, you will own agent features end to end — from problem definition and design, to shipping, to measuring and improving quality in production. What You’ll Work On You will contribute to the design, development, and productionization of one or more enterprise AI agents, including: Marketing Agent: Empower marketers to improve conversion rates and drive revenue growth. Strategy Agent: Transform raw data into actionable, revenue-driving strategies and high-potential audience segments. Data Analysis Agent: Answer business questions by planning multi-step analyses and running SQL over large customer datasets, with every number traceable to the query that produced it. Sales and Service Agent: Drive sales conversion, increase average order value (AOV), and deepen brand engagement and customer loyalty through real-time, 24/7 AI-powered support. Build agent capabilities as reusable skills and MCP tools, and design tool interfaces that agents use correctly and efficiently Bring predictive models (e.g. propensity, churn, recommendation) into agent workflows and next-best-action suggestions Build evaluation — test sets, LLM-as-a-judge, production trace review — and use it to decide what ships Make agents faster and cheaper without losing answer quality, through c

Our Perception team is responsible for using our sensor data to understand the complex and dynamic environments where we drive. In this role, you will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms. We are creating new algorithms for segmentation, tracking, classification, and high-level scene understanding, and you could work on any (or all!) of these components. As a Senior Staff ML Engineer, you will lead the development of machine learning algorithms that can range in influence from onboard autonomy to offboard autonomy and validation. You will collaborate closely with other teams specializing in Prediction, Planning, Simulation, and Safety Validation, influencing our overall technical stack. Your role will look at problems in a way that crosses team boundaries to prototype new approaches that influence the long term technical direction of multiple organizations within the company. The impact of the role can be in the form of impacting immediate company milestones to leading forward-looking exploratory projects. Responsibilities Develop new algorithms to understand the scene around the robot, and how that scene would evolve through time Build multi-modal foundation models for on-vehicle and offline applications Develop new algorithms to apply generative AI to simulation to improve the realism of our offline validation systems Leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field Provide technical mentorship to the broader group of ML developers at Zoox Collaborate with engineers on Prediction, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying Deep Learning models on sensor data-Experience

Work Experience Required: 8 - 12 Years Experience in programing (Python, R, SQL, NoSQL,Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as numpy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction. Proven ability to discover solutions hidden in large datasets and to drive business results with their data-based insights Drive excellent project management required to deliver complex projects, including effort/time estimation. Be proactive, with full ownership of the engagement. Build scalable client engagement level processes for faster turnaround & higher accuracy Define Technology/ Strategy and Roadmap for client accounts, and guides implementation of that strategy within projects Run regular project reviews and audits to ensure that projects are being executed within the guardrails agreed by all stakeholders Manage the team-members, to ensure that the project plan is being adhered to over the course of the project Manage the client stakeholders, and their expectations, with a regular cadence of weekly meetings and status updates. Build a trusted advisor relationship with the IT management at clients and internal accounts leadership. Build

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Data Science is an integral component of Coinbase’s product and decision making process: we work in partnership with Product, Engineering and Design to influence the roadmap and better understand our users. With a deep expertise in experimentation, analytics and advanced modeling, we produce insights which directly move the company’s bottom line. What you'll be doing: Conduct analysis and deep dives on ambiguous problems for our business. Your work will result in insights and recommendations that guide the team’s decision making. Build, tune, or measure the performance of online and offline ML models and AI systems used across Coinbase. Act as owner for a broad scope of data and metrics, from definitions and core logging to presentation of data visualizations. Guide code reviews, provide SQL and Python expertise, and create well-maintained ETL jobs. Maintain a high bar for statistical rigor on your team. Design, execute, and uplevel experimentation and causal analyses that build confidence with your stakeholders. What we look for in you: A BA/BS in a quantitative field (ex Math, Stats, Physics, or Computer Science) with ≥5+ years of relevant experience or a PhD in a quantitative field with with ≥3+ years of relevant experience Demonstrated experience in driving impactful data science projects that tackle ambiguous problem spaces. Ability to in