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machine learning engineer

Mercor

<div>
 
 About Mercor
 
 
 
 Mercor is at the intersection of labor markets and AI research. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development.
 
 
 Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.
 
 
 Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You&rsquo;ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society.
 
 
 Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our new San Francisco headquarters.
 
 
 
 About The Role
 
 
 
 As a Machine Learning Engineer at Mercor, you&rsquo;ll operate at the intersection of backend engineering and applied machine learning. ML Engineers at Mercor are generalists first, shipping production systems that power performance prediction, search, recommendation, and fraud detection while also bringing statistical and modeling rigor where it matters. The work spans everything from building APIs and infrastructure to training and deploying models, always tied closely to core product outcomes. You&rsquo;ll collaborate with product engineers and operations to deliver systems that directly impact how companies source talent and how candidates find opportunities
 
 
 
 You Will
 
 
 
 <ul>
 <li>
 Research, train, and productionize ML models for engagement prediction, scoring, search
 </li>
 <li>
 Build backend infrastructure and APIs to serve ML models reliably at scale.
 </li>
 <li>
 Run experiments, analyze results, and iterate quickly to improve both models and product performance.
 </li>
 <li>
 Work cross-functionally with Operations and Product to translate business needs into model-driven solutions.
 </li>
 <li>
 Wear many hats: from backend engineer to applied ML practitioner to product problem-solver.
 
 
 </li>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 <ul>
 <li>
 Strong backend engineering skills (ex. Python/Django or similar) plus a solid foundation in applied ML and statistics.
 </li>
 <li>
 Proven experience shipping production systems or ML-driven products end-to-end.
 </li>
 <li>
 High ownership and comfort operating in ambiguous, fast-changing environments.
 </li>
 <li>
 Generalist mindset: willing to flex between backend, modeling, data pipelines, and product problem-solving.
 
 
 </li>
 </ul>
 
 Why Mercor
 
 
 
 <ul>
 <li>
 Impact: Your work powers how the world&rsquo;s leading AI labs train and test their models.
 </li>
 <li>
 Learning: Get early insights into frontier model capabilities months before the market.
 </li>
 <li>
 Growth: Work on both infrastructure and research-adjacent projects with fast paths to ownership.
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Generous equity grant vested over 4 years
 </li>
 <li>
 A $20K relocation bonus (if moving to the Bay Area)
 </li>
 <li>
 A $10K housing bonus (if you live within 0.5 miles of our office)
 </li>
 <li>
 A $1K monthly stipend for meals
 </li>
 <li>
 Free Equinox membership
 </li>
 <li>
 Health insurance
 
 
 </li>
 </ul>
 Compensation Range: $130K - $500K
 
 
</div>

Machine Learning Engineer

Baselayer

<div>
 
 
 About Baselayer:
 
 
 
 Trusted by 2,200+ financial institutions, Baselayer is the intelligent business identity platform that helps verify any business, automate KYB, and monitor real-time risk. Baselayer&rsquo;s B2B risk solutions &amp; identity graph network leverage state &amp; federal government filings and proprietary data sources to prevent fraud, accelerate onboarding, and lower credit losses.&nbsp;
 
 
 &nbsp;
 
 
 
 About You:
 
 
 
 You want to learn from the best of the best, get your hands dirty, and put in the work to hit your full potential. You're not just doing it for the win&mdash;you're doing it because you have something to prove and want to be great. You are looking to be an impeccable machine learning engineer working on cutting-edge AI solutions.
 
 <ul>
 <li>
 You have 4-8 years of experience in machine learning development, working with Python and building ML models
 </li>
 <li>
 You're comfortable working with large-scale data and enjoy optimizing performance for computationally intensive ML systems
 </li>
 <li>
 You have a strong foundation in AI/ML fundamentals, particularly with LLMs, and are eager to experiment with emerging techniques
 </li>
 <li>
 You prioritize responsible AI practices and model governance, especially in regulated environments like KYC/KYB
 </li>
 <li>
 You have a keen eye for detail and take pride in writing clean, maintainable code while optimizing for model performance
 </li>
 <li>
 You thrive in a high-trust, ownership-focused environment and are comfortable working across different levels of abstraction
 </li>
 <li>
 Problem-solver who navigates the unknown confidently
 </li>
 <li>
 Proactive self-starter who thrives in dynamic settings
 </li>
 <li>
 Incredibly intelligent and clever. You take pride in your models
 </li>
 <li>
 Highly feedback-oriented. We believe in radical candor and using feedback to get to the next level
 </li>
 </ul>
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Model Development &amp; Integration: Build and maintain ML models and integrate them with various data sources, ensuring scalability, high performance, and adaptability for autonomous agents in the GTM space
 </li>
 <li>
 ML System Design: Architect and design core ML services that support KYC/KYB processes, leveraging knowledge graphs and LLMs for dynamic use cases
 </li>
 <li>
 Data Processing &amp; Feature Engineering: Develop and maintain robust data pipelines for feature extraction and transformation, focusing on scalability and performance when handling large-scale, high-dimensional data
 </li>
 <li>
 Advanced ML Techniques: Implement and experiment with state-of-the-art techniques including reinforcement learning from human feedback (RLHF) and parameter-efficient fine-tuning methods (e.g., LoRA) to improve LLMs for specific use cases within the identity space
 </li>
 <li>
 ML Infrastructure: Build and maintain infrastructure for model training, evaluation, and deployment, creating a scalable platform foundation for continued innovation
 </li>
 <li>
 Model Governance &amp; Compliance: Ensure ML systems meet industry standards for fairness, explainability, and compliance, particularly around KYC/KYB regulations
 </li>
 <li>
 Performance Optimization: Implement optimizations for model inference and training, ensuring ML services can efficiently process identity data while maintaining reliability
 </li>
 <li>
 Experimentation &amp; Evaluation: Design and conduct experiments to evaluate model performance, debug issues, and monitor ML services, while continuously improving architectures to handle diverse data and use cases
 </li>
 </ul>
 
 &nbsp;
 
 
 
 Work Location
 
 
 <ul>
 <li>
 Hybrid in SF. In office 3 days/week
 </li>
 </ul>
 
 &nbsp;
 
 
 &nbsp;
 
 
 
 Compensation and Benefits
 
 
 <ul>
 <li>
 
 Salary range of $145,000 to $225,000
 
 </li>
 <li>
 
 Equity package
 
 </li>
 <li>
 
 Unlimited vacation
 
 </li>
 <li>
 
 Fully paid health insurance, dental, and vision
 
 </li>
 <li>
 
 401(k) with company match
 
 </li>
 </ul>
 
 &nbsp;
 
</div>

Reducto

<div>
 
 About Reducto
 
 
 
 Reducto helps AI teams ingest real world enterprise data with state of the art accuracy.
 
 
 The vast majority of enterprise data &mdash; from financial statements to health records &mdash; is locked in unstructured file formats like PDFs and spreadsheets. We train vision models to read those documents the way a human would, and make it possible to build products, train models, and automate processes at scale.
 
 
 We&rsquo;ve grown incredibly quickly, growing revenue by 7x YOY, and now work with hundreds of companies ranging from leading AI teams (Harvey, Vanta, Scale), through to enterprise (FAANG, top 3 trading firm).
 
 
 We've raised over 100M from world class investors like A16z, Benchmark, and First Round Capital, and are hiring a Machine Learning Engineer to help us train and deploy the models critical to the performance of our core product.
 
 
 
 
 We Would Love To Meet You If You:
 
 
 
 
 <ul>
 <li>
 Philosophy: You are your own worst critic. You have a high bar for quality and don&rsquo;t rest until the job is done right&mdash;no settling for 90%. We want someone who ships fast, with high agency, and who doesn't just voice problems but actively jumps in to fix them.
 </li>
 <li>
 Experience: You have 2+ years of experience with training, fine tuning, and evaluating ML models used in production systems
 </li>
 <li>
 Language/Skills: You&rsquo;re exceptional at Python or similar, and are well versed with both traditional computer vision and VLMs
 </li>
 <li>
 Tools: Build your own tools as needed&mdash;like a quick Streamlit app to test hypotheses or create a dataset.
 </li>
 <li>
 Approach: A quantitative approach to building products. Ability to debug, experiment, and iterate fast. You should be comfortable getting hands-on with the full development lifecycle, from ideation to shipping to users.
 
 
 </li>
 </ul>
 
 The Core Work Will Include:
 
 
 
 <ul>
 <li>
 Training and deploying new state of the art models for parsing and interpreting unstructured data
 </li>
 <li>
 Experimenting with novel techniques to improve LLM accuracy
 </li>
 <li>
 Build data pipelines, evaluate model performance, and integrate models into the product
 </li>
 <li>
 Working directly with the founders and customers to shape the product direction and engineering strategy
 
 
 </li>
 </ul>
 
 Bonus Points If You:
 
 
 
 <ul>
 <li>
 Have prior experience founding a company or building products at early stages
 </li>
 <li>
 Are ambitious and driven, and care a lot about doing great work with great people
 </li>
 <li>
 Keep up with the latest developments in ML/AI
 
 
 </li>
 </ul>
 This is an in person role at our office in SF. We&rsquo;re an early stage company which means that the role requires working hard and moving quickly. Please only apply if that excites you.
 
 
 
 About Reducto
 
 
 
 
 Nearly 80% of enterprise data is in unstructured formats like PDFs
 
 
 
 PDFs are the status quo for enterprise knowledge in nearly every industry. Insurance claims, financial statements, invoices, and health records are all stored in a structure that&rsquo;s simply impractical for use in digital workflows. This isn&rsquo;t an inconvenience&mdash;it&rsquo;s a critical bottleneck that leads to dozens of wasted hours every week.
 
 
 
 Traditional approaches fail at reliably extracting information in complex PDFs
 
 
 
 OCR and even more sophisticated ML approaches work for simple text documents but are unreliable for anything more complex. Text from different columns are jumbled together, figures are ignored, and tables are a nightmare to get right. Overcoming this usually requires a large engineering effort dedicated to building specialized pipelines for every document type you work with.
 
 
 
 Reducto
 
 
 Breaks Document Layouts Into Subsections And Then Contextually Parses Each Depending On The Type Of Content.
 
 This Is Made Possible By a Combination Of Vision Models, LLMs, And a Suite Of Heuristics We Built Over Time. Put Simply, We Can Help You:
 
 
 <ul>
 <li>
 Accurately extract text and tables even with nonstandard layouts
 </li>
 <li>
 Automatically convert graphs to tabular data and summarize images in documents
 </li>
 <li>
 Extract important fields from complex forms with simple, natural language instructions
 </li>
 <li>
 Build powerful retrieval pipelines using Reducto&rsquo;s document metadata
 </li>
 <li>
 Intelligently chunk information using the document&rsquo;s layout data
 
 
 </li>
 </ul>
 Benefits at Reducto
 
 
 
 At Reducto, we&rsquo;re invested in the well-being and growth of our team. Here&rsquo;s what we currently offer:
 
 
 
 <ul>
 <li>
 Unlimited PTO: We believe great work requires recharging.
 </li>
 <li>
 Lunch: Receive a free lunch to eat with your teammates daily at the office
 </li>
 <li>
 Reimbursed Transportation: Provide us with your receipts and we&rsquo;ll take care of the costs
 </li>
 <li>
 Insurance: Generous health insurance covering medical, dental, and vision.
 </li>
 <li>
 Health and Wellness Budget: We provide up to $150/mo reimbursement for health and wellness spending, such as gym memberships, fitness classes, or similar.
 </li>
 <li>
 Parental Leave: Work with us to build a leave schedule that works for you and your family
 
 
 </li>
 </ul>
 Reducto is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law.
</div>

Apple

iPhone is the most popular camera in the world, with billions of photos taken every year. The seamless hardware-software integration consistently pushes mobile photography boundaries. Features like the Photonic Engine, Portrait mode, and Super-high-resolution photos transform moments into magical experiences that delight our customers globally. 
 
The Camera Technologies &amp; Systems team, within Camera &amp; Photos org, delivers unparalleled image and video experiences by innovating at the intersection of state-of-the-art machine learning and computer vision. As a Senior Machine Learning Engineer, you&rsquo;ll pioneer research and develop groundbreaking generative AI for image enhancement and restoration. Your work will enable new camera capabilities across the Apple ecosystem. Every &quot;Shot on iPhone&quot; billboard showcases our ingenuity; we invite you to join our mission and contribute to a world-renowned visual narrative. 
 
Description 
 
As a Machine Learning Engineer, you will be instrumental in driving the innovation of Apple's next-generation iPhone and iPad camera algorithms. You will identify, research, and develop cutting-edge generative AI-based machine learning models to address complex challenges in camera applications. You will collaborate cross-functionally with GPU optimization and framework teams to seamlessly integrate and deploy these advanced features into production, directly shaping the future of mobile imaging. 
 
Preferred Qualifications 
 
Advanced Generative AI Applications: Extensive practical experience in the design, training, and fine-tuning of complex generative AI architectures, encompassing diffusion models, autoregressive models, GANs, and VLMs. Demonstrated success in optimizing and deploying generative models is a plus. 
 
Computer Vision Foundation: Robust theoretical and practical foundation in core computer vision principles, particularly applied to image and video enhancement and restoration tasks such as denoising, super-resolution, and in-painting. 
 
Analytical &amp; Communication Skills: Exceptional analytical problem-solving capabilities and technical communication skills, essential for cross-functional collaboration and presenting complex research. 
 
Proven Research: Publication record in highly selective, peer-reviewed conferences (e.g., CVPR, ICCV, ECCV, SIGGRAPH, NeurIPS, ICML, ICLR) 
 
Minimum Qualifications 
 
Generative AI Expertise: In-depth understanding and practical experience with advanced generative AI architectures, including (but not limited to) diffusion models, Generative Adversarial Networks (GANs), and autoregressive models. 
 
ML Development Lifecycle: Demonstrated industry experience in the full lifecycle development, optimization, and deployment of machine learning models. 
 
Technical Proficiency: Strong programming skills in Python and deep learning frameworks (e.g., PyTorch). 
 
An MS or PhD in Computer Science, Engineering, or a related technical discipline. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Camera and Photos - Machine Learning Engineer

Are you a passionate Machine Learning Engineer with a deep love for photography? Join Apple's Camera Hardware Engineering team and help us redefine the camera experience for millions of users worldwide. As a key player in our innovative team, you will collaborate closely with hardware, software, and image processing specialists to develop cutting-edge camera technologies. 
 
Description 
 
As a Machine Learning Engineer in the Camera Hardware Engineering group you will be responsible for all research, design, development, test, and qualification of camera hardware for Apple products. This team is seeking an experienced Machine Learning Engineer with a background in Camera and image sensor technologies. You will bring your expertise to the team and be responsible for ongoing design, evaluation, benchmarking and characterization of Apple camera products.&quot;,&quot;responsibilities&quot;:&quot;ML Algorithms: Research, design, and implement machine learning algorithms for various camera tasks, including image and video processing, computational photography, and scene understanding. 
 
Data-Driven Development: Collaborate with data collection teams to curate large-scale image and video datasets and perform data analysis and preprocessing to train and validate your ML models effectively. 
 
Prototyping and Evaluation: Develop prototypes of ML algorithms and evaluate their performance through rigorous testing and user feedback. Your insights will drive continuous improvement. 
 
Preferred Qualifications 
 
MS or Ph.D. in Machine Learning, EE, CS, Physics, Optics, or equivalent and 3+ years of experience in machine learning research or relevant industry experience 
 
Experience with applying deep learning to various computer vision tasks, such as: Object recognition, Image segmentation, Inpainting, and Anomaly detection 
 
Experience in applying generative AI and reinforcement learning techniques to enhance hardware design processes. 
 
Experience with using advanced ML methods to optimize system architectures and improve image quality in the hardware design domain. 
 
Experience with image quality metrics and evaluation methodology 
 
Experience with camera components, functions, and the camera ISP pipeline 
 
Experience with megapixel CMOS image sensor technology, lens selection, and qualification 
 
Minimum Qualifications 
 
Bachelor&rsquo;s degree in Computer Science, Electrical Engineering, Physics, Optics, or a related field 
 
Experience with Python programming and deep learning frameworks like PyTorch 
 
Experience with machine learning and computer vision principles, and algorithms. 
 
Experience with camera and/or image sensor technologies. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Camera Machine Learning Engineer - Camera Hardware

Hayden AI

<div>
 
 About Us
 
 
 
 At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.
 
 
 From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.
 
 
 
 Job Title:
 
 Machine Learning Operations Engineer
 
 
 
 Company:
 
 Hayden AI Technologies, Inc.
 
 
 
 Location:
 
 460 Bryant Street, Suite 100, San Francisco, CA 94107
 
 
 
 Position Duties
 
 
 
 <ul>
 <li>
 Optimize orchestration processes to ensure efficient deployment and management of AI models.
 </li>
 <li>
 Implement cost-saving strategies to minimize infrastructure expenses while maximizing performance.
 </li>
 <li>
 Upgrade throughput to enhance scalability and responsiveness of AI systems.
 </li>
 <li>
 Collaborate with cross-functional teams to identify bottlenecks and implement solutions to improve workflow efficiency.
 </li>
 <li>
 Ship new features and updates rapidly while maintaining high levels of quality and reliability.
 </li>
 <li>
 Deploy and monitor machine learning models produced by deep learning engineers.
 </li>
 <li>
 Design, deploy, and maintain performant and scalable processes for data acquisition and manipulation to enhance dataset accessibility.
 </li>
 <li>
 Participate actively in the team's software development process, including design reviews, code reviews, and brainstorming sessions.
 </li>
 <li>
 Maintain accurate and updated software development documentation.
 
 
 </li>
 </ul>
 
 Degree Requirements
 
 
 
 Bachelor of Science or Engineering degree or a foreign equivalent in Robotics, Machine Learning, Computer Science, Electrical Engineering, Electronics and Telecommunication Engineering, or a related field.
 
 
 
 Experience Requirement
 
 
 
 One (1) year of work experience in the job offered or as a Deep Learning Engineer, Perception Engineer II, MLOps, Research Engineer II, Machine Learning, Computer Vision Intern, or another related deep learning engineer role.
 
 
 
 Other Special Requirements
 
 
 
 <ul>
 <li>
 One (1) year of work experience with all of the following:
 </li>
 <ul>
 <li>
 Deploying real-world applied computer vision (including deep learning models) on edge devices
 </li>
 <li>
 Python programming and software design
 </li>
 <li>
 C++
 </li>
 <li>
 Software development tools and libraries including PyTorch, OpenCV, TensorFlow, MLflow
 </li>
 <li>
 Automated data annotation
 </li>
 <li>
 Distributed training in the cloud
 </li>
 <li>
 Deploying and managing GPU clusters for ML pipelines and workflows
 
 </li>
 </ul>
 </ul>
 
 Rate of Pay:
 
 $135,699.00 to $190,000.00 per year
 
 
 
 Location of Position and Interview:
 
 
 
 Hayden AI Technologies, Inc.
 
 
 460 Bryant Street, Suite 100
 
 
 San Francisco, CA 94107
 
 
 
 Applicants Should Submit Resumes To
 
 
 
 Janet Le-Mcintosh
 
 
 janet.le@hayden.ai
 
 
 Hayden AI Technologies, Inc.
 
 
 460 Bryant Street, Suite 100
 
 
 San Francisco, CA 94107
</div>

Machine Learning Operations Engineer

J&T Business Consulting

<div><div><div>Company: Confidential Client 
</div><div>Location: San Francisco, CA (Hybrid) 
</div><div>Salary: $240,000 &ndash; $380,000 base + equity + bonus 
</div><div>Recruitment Partner: J&amp;T Recruitment &ndash; Exclusively Retained 
</div>J&amp;T Recruitment has been exclusively retained by a rapidly scaling AI technology company in San Francisco that is building cutting-edge generative AI platforms used by global enterprise clients. 
They are seeking a Senior AI Engineer to design and deploy production-grade machine learning systems and contribute to the architecture of next-generation AI products.<h3 class="jobSectionHeader"> 
Key Responsibilities</h3> 
<ul><li>Design, train, and deploy large-scale machine learning and generative AI models</li> 
<li>Build scalable data pipelines for model training and inference</li> 
<li>Develop production-ready ML services and APIs</li> 
<li>Work closely with product managers and data scientists to translate research into production systems</li> 
<li>Optimize models for performance, cost, and latency</li> 
<li>Contribute to the design of distributed AI infrastructure</li> 
<li>Stay up to date with advancements in LLMs, transformer architectures, and generative AI</li> 
</ul><h3 class="jobSectionHeader">Tech Stack</h3> 
<ul><li>Python</li> 
<li>PyTorch / TensorFlow</li> 
<li>Hugging Face / Transformers</li> 
<li>Kubernetes</li> 
<li>AWS / GCP</li> 
<li>Vector databases</li> 
<li>ML pipelines (Airflow / Kubeflow)</li> 
</ul><h3 class="jobSectionHeader">Requirements</h3> 
<ul><li>5+ years of experience in Machine Learning or AI Engineering</li> 
<li>Strong experience building and deploying ML models to production</li> 
<li>Experience working with LLMs, NLP, or generative AI systems</li> 
<li>Strong programming skills in Python</li> 
<li>Experience with distributed systems and cloud platforms</li> 
</ul><h3 class="jobSectionHeader">Interview Process</h3> 
<div><ul><li>Recruiter Screening (30 minutes) &ndash; Introduction via J&amp;T Recruitment</li></ul> 
<ul><li>Technical Coding Interview (60 minutes) &ndash; Python and ML fundamentals</li></ul> 
<ul><li>Machine Learning System Design (90 minutes) &ndash; Designing scalable ML architecture</li></ul> 
<ul><li>Technical Deep Dive (90 minutes) &ndash; Discussion around previous AI projects</li></ul> 
<ul><li>Final Leadership Interview (45 minutes) &ndash; Cultural and team alignment</li></ul></div></div></div><div></div>

Senior AI Engineer

Explore 177+ Machine learning engineer in San Francisco this March. Find roles across top companies and apply now to boost your career.

177 machine learning engineer jobs In San Francisco

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Camera and Photos - Machine Learning Engineer

Camera Machine Learning Engineer - Camera Hardware

Machine Learning Operations Engineer

Senior AI Engineer