Machine Learning Engineer Jobs in San Francisco, USA

About Us At Agtonomy, we’re not just building tech—we’re transforming how vital industries get work done. Our Physical AI and fleet services turn heavy machinery into intelligent, autonomous systems that tackle the toughest challenges in agriculture, turf, and beyond. Partnering with industry-leading equipment manufacturers, we’re creating a future where labor shortages, environmental strain, and inefficiencies are relics of the past. Our team is a tight-knit group of bold thinkers—engineers, innovators, and industry experts—who thrive on turning audacious ideas into reality. If you want to shape the future of industries that matter, this is your shot. About the Role We're looking for a skilled ML engineer to build the perception systems that give our autonomous machines human-like awareness in rugged, unstructured environments. You'll develop computer vision and machine learning systems that turns noisy camera and LiDAR data into robust 3D scene understanding — enabling heavy equipment to operate safely through dust, glare, occlusion, and whatever messy conditions a working site throws at it. The field is moving past bounding-box detection and hand-tuned tracking toward learned, dense scene representations, foundation-model-driven data engines, and uncertainty-aware perception. You'll be at the center of that shift. This role is hands-on: you'll write production-grade software, distill and optimize models for embedded hardware, and validate your work on real machines at operating around the world.

Machine Learning Engineer: Perception Analytics at Bedrock robotics. Apply via Ashby.

<p><strong>About the Role</strong><br><br>The Shopping Ranking Team mission is enabling eaters to effortlessly make shopping decisions and find what they need. We pursue this mission via an ML-driven algorithmic approach, applying state-of-the-art Machine Learning (ML), Optimization techniques to learn from massive datasets Uber has, and build a scalable and reliable shopping intelligence ranking and recommendation systems. We are actively seeking individuals who excel in problem-solving and critical thinking, are proficient in coding, with proven track records of learning and growth, and have a deep interest in ML model, feature and infrastructure development. Candidates will have the opportunity to work across various lines, from infrastructure development to ML model development, productionalization, offering a diverse and enriching experience. Join us in our pursuit of excellence as we are building the next generation of shopping ranking and recommendation systems.<br><br><strong>What the Candidate Will Need / Bonus Points</strong><br><br>---- What the Candidate Will Do ----<br><br><ul><li>Design and build Machine Learning models in Ranking and Recommendation domain.</li><li>Productionize and deploy these models for real-world application.</li><li>Review code and designs of teammates, providing constructive feedback.</li><li>Collaborate with Product and cross-functional teams to brainstorm new solutions and iterate on the product.</li></ul><br>---- Basic Qualifications ----<br><br><ul><li>Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 4+ years of full-time engineering experience.</li><li>2+ years of ML experience and building ML models</li><li>Experience working with multiple multi-functional teams(product, science, product ops etc).</li><li>Expertise in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).</li><li>Experience with big-data architecture, ETL frameworks and platforms, such as HDFS, Hive, MapReduce, Spark, , etc.</li><li>Working knowledge of latest ML technologies, and libraries, such as PyTorch, TensorFlow, Ray, etc.</li><li>Proven track records of being a fast learner and go-getter, with willingness to get out of the comfort zone.</li></ul><br>---- Preferred Qualifications ----<br><br><ul><li>Experience with building ranking and recommendation systems in production, making practical tradeoffs among algorithm sophistication, compute complexity, maintainability, and extensibility in production environments.</li><li>Experience with taking on vague business problems, translating them into ML + Optimization formulation, identifying the right features, model structure and optimization constraints, and delivering business impact.</li><li>Experience with design and architecture of ML systems and workflows.</li><li>Experience owning and delivering a technically challenging, multi-quarter project end to end.</li></ul><br>For New York, NY-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.<br><br>For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.<br><br>For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.<br><br>For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.<br><br>Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.<br><br>Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.</p>

<p>On any given day at Disney Entertainment &amp; ESPN Technology, we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories while also transforming Disney’s media business for the future. Whether that’s evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to maximize flexibility and efficiency, or delivering Disney’s unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world.</p> <p></p> <p><i>A few reasons why we think you’d love working for Disney Entertainment &amp; ESPN Technology</i></p> <ul><li><b>Building the future of Disney’s media business: </b>DE&amp;E Technologists are designing and building the infrastructure that will power Disney’s media, advertising, and distribution businesses for years to come.</li><li><b>Reach &amp; Scale:</b> The products and platforms this group builds and operates delight millions of consumers every minute of every day – from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more.</li><li><b>Innovation:</b> We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment &amp; news.</li></ul> <p></p> <p>Our team is responsible for developing, implementing, and maintaining Hulu's recommendation and personalization algorithms. As part of this team, you will collaborate with Engineering, Product, and Data teams to apply machine learning techniques to achieve strategic personalization goals. This is an Individual Contributor role in content recommendations. You will be expected to lead recommendation and personalization algorithm research, development, implementation, and optimization for product areas, and to coordinate requirements and manage stakeholder expectations with Product, Engineering, and Editorial teams. As an IC, you will also be responsible for helping to set the roadmap for algorithmic work — not only for how to approach product requests for new recommendation features, but for helping to drive larger company objectives in the areas of personalization and content recommendation.</p> <p></p> <p><b>Responsibilities:</b></p> <ul><li><b>Algorithm Development and Maintenance:</b> Utilize cutting edge machine learning methods to develop algorithms for personalization, recommendation, and other predictive systems and bring it to large-scale real-time recommendation pipeline; maintain algorithms deployed to production and be the point person in explaining methodologies to technical and non-technical teams</li><li><b>Feature Engineering and Optimization</b>: Develop and maintain ETL pipelines using orchestration tools; deploy scalable streaming and batch data pipelines to support petabyte scale datasets</li><li><b>Development Best Practices</b>: Maintain existing and establish new algorithm development, testing, and deployment standards</li><li><b>Collaborate with product and business stakeholders</b>: Identify and define new personalization opportunities with product team and work with data teams to improve how we do data collection, experimentation and analysis</li><li><b>Strong written and verbal communication skills</b></li></ul> <p></p> <h2><span>Basic Qualification:</span></h2> <ul><li>Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience</li><li>In-depth understanding of deep learning technology in recommendation system or NLP fields</li><li>Proficiency in at least one of the following deep learning framework, tensorflow, pytorch</li><li>Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark</li><li>Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment</li><li>Ability to articulate the usage and behavior of models and algorithms to both technical and non-technical audiences</li><li>7+ years of experience in developing highly scalable machine learning products</li><li>7+ years writing production-level, scalable Python codes</li></ul> <p></p> <h2><span>Preferred qualification:</span></h2> <ul><li>MS or PhD in statistics, math, computer science, or related quantitative field</li><li>Familiarity with Java and/or Scala programming languages</li><li>Production experience with developing content recommendation algorithms at scale and familiar with metadata management, data lineage, and principles of data governance</li><li>Building streaming data pipelines using Kafka, Spark, or Flink</li></ul> <p></p> <p>#DISNEYTECH</p> <p><br>The hiring range for this position in New York, NY &amp; Seattle, WA is $172,300-$231,100 per year, in San Francisco, CA is $180,200.00 to $241,600.00 per year and in Los Angeles, CA is $164,500.00 to $220,600.00 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.</p>

<p><strong>About the Team:</strong><br> <br>The Applied AI team collaborates with product teams across Uber to deliver innovative AI solutions for core business problems. We work closely with engineering, product and data science teams to understand core business problems and the potential for AI solutions, then deliver those AI solutions end-to-end. Key areas of expertise include Personalization, Generative AI, Computer Vision, ML Optimization and Geospatial AI.<br> <br><strong>About the Role:</strong><br> <br>We are building AI-native discovery experiences across Mobility and Delivery. Search, recommendations, and conversational AI are central to how millions of users discover rides, restaurants, grocery items, and retail products every day. We are hiring a Staff ML Engineer (IC6) to define and lead the foundation model strategy powering these experiences.<br> <br>At this level, you will not just build models - you will shape technical direction across teams, influence product strategy, and deliver measurable impact at global scale.<br> <br><strong>What the Candidate Will Do</strong><br> <ul> <li>Own the end-to-end technical strategy for foundation models across Search, Recommendations, and Conversational AI.</li> <li>Drive architecture decisions that influence multiple product surfaces (Eats, Grocery, Retail, Mobility).</li> <li>Lead cross-team initiatives spanning Retrieval, Ranking, Personalization, and LLM-powered assistants.</li> <li>Define long-term investment areas (build vs fine-tune vs partner models).</li> <li>Mentor senior engineers and act as a technical multiplier across the org.</li> </ul> <br><strong>Basic Qualifications</strong><br> <ul> <li>Masters degree or Ph.D in Computer Science, Engineering, Mathematics </li> <li>8+ years of ML experience, including significant work on large-scale deep learning systems.</li> <li>Demonstrated ownership of high-impact ML systems in search, recommendations, or conversational AI.</li> <li>Deep expertise in transformers, retrieval systems, ranking, and embedding architectures.</li> <li>Strong experience with PyTorch and distributed training .</li> <li>Track record of influencing technical direction across teams.</li> <li>Strong product intuition and ability to connect model improvements to business outcomes.</li> </ul> <br><strong>Preferred Qualifications</strong><br> <ul> <li>Experience leading multi-team ML initiatives.</li> <li>Defined long-term technical roadmaps adopted across orgs.</li> <li>Elevated engineering standards through mentorship and technical leadership.</li> </ul> <br> ~~ ~~ <br><br>For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.<br> <br>For Seattle, WA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.<br> <br>For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.<br> <br>For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.<br> <br><strong>Ready to Ride?</strong><br> <br>This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.<br> <br>You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits. <br> <br>Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.<br> <br>Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.</p>

Machine Learning Engineer - Multimodal Modeling at Standinsurance. Apply via Ashby.

Senior Machine Learning Engineer at Evenup. Apply via Ashby.

Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign’s next generation of intelligent systems. You will bridge the gap between core AI research and production-grade engineering, developing scalable platforms for autonomous agents, advanced retrieval systems, and automated model optimization. This position is an individual contributor role reporting to the Director, Machine Learning Engineering. Responsibility Build and maintain high-performance distributed systems to support large-scale model inference and data processing Design frameworks for multi-agent systems, focusing on state management, reliability, and long-running autonomous workflows Architect sophisticated Retrieval-Augmented Generation (RAG) pipelines and advanced context management strategies to improve model accuracy and relevance Develop platform-level tools for automated prompt engineering, evaluation, and optimization to accelerate the AI development lifecycle Implement robust ML pipelines, focusing on observability, versioning, and the seamless deployment of generative AI services Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law. What you bring Basic 5+ years of experience in machine learning engineering, software engineering, or related operational roles Experience in software engineering with a focus on distributed systems and scalable backend architecture Deep understanding of the ML lifecycle, from data ingestion and training to production monitoring Experience building with LLMs, including RAG architectures and sophisticated prompt engineering Experience deploying and maintaining ML models in high-traffic, production environments Expertise in Python and experience with modern ML frameworks such as PyTorch Preferred Experience with distributed task queues or stateful workflow engines for managing complex, multi-step AI processes Experience with frameworks designed for horizontal scaling of compute-intensive ML workloads Experience designing "agent-loop" architectures that involve tool-use, self-correction, and multi-step reasoning Familiarity with vector storage systems and high-throughput data processing pipelines Wage Transparency Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience. Based on applicable legislation, the below details pay ranges in the following locations: California: $164,700.00 - $266,000.00 base salary Washington: $158,300.00 - $232,575.00 base salary This role is also eligible for the following: Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance. Stock: This role is eligible to receive Restricted Stock Units (RSUs). Global benefits provide options for the following: Paid Time Off: earned time off, as well as paid company holidays based on region Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment Retirement Plans: select retirement and pension programs with potential for employer contributions Learning and Development: options for coaching, online courses and education reimbursements Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance. Applicant and Candidate Privacy Notice States Not Eligible for Employment This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming. Equal Opportunity Employer It's important to us that we build a talented team that is as diverse as our customers and where all employees feel a deep sense of belonging and thrive. We encourage great talent who bring a range of perspectives to apply for our open positions. Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can-do approach. We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category. EEO Know Your Rights poster #LI-Hybrid