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machine learning engineer

Aarki

<div>
 
 Who are we?
 
 
 
 Aarki is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.
 
 
 
 The role?
 
 
 
 We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with Senior MLE and other team members to drive impactful machine learning projects and contribute to innovative solutions.
 
 
 
 What will you do?
 
 
 
 <ul>
 <li>
 Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.
 </li>
 <li>
 Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.
 </li>
 <li>
 Analyze the impact of integrating new data sources and features into our models.
 </li>
 <li>
 Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.
 </li>
 <li>
 Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.
 </li>
 <li>
 Document experiments, assumptions, and outcomes; maintain reproducibility
 
 
 </li>
 </ul>
 
 What are we looking for?
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Mathematics, Physics, Computer Science, or a related technical field.
 </li>
 <li>
 At least 2 years of professional experience in machine learning, statistical analysis, and data analysis.
 </li>
 <li>
 Experience with machine learning techniques such as regression, classification, and clustering.
 </li>
 <li>
 Proficiency in Python and SQL and familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
 </li>
 <li>
 Strong grasp of probability, statistics, and data analysis principles.
 </li>
 <li>
 Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders.
 
 
 </li>
 </ul>
 Nice-to-Have
 
 
 <ul>
 <li>
 Familiarity with system programming languages including C++ and Rust is a plus.
 </li>
 <li>
 Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink)
 </li>
 <li>
 Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.
 </li>
 </ul>
</div>

Machine Learning Engineer

Liftoff

<div><div>Liftoff is a leading AI-powered performance marketing platform for the mobile app economy. Our end-to-end technology stack helps app marketers acquire and retain high-value users, while enabling publishers to maximize revenue across programmatic and direct demand.

Liftoff's solutions, including Accelerate, Direct, Monetize, Intelligence, and Vungle Exchange, support over 6,600 mobile businesses across 74 countries in sectors such as gaming, social, finance, ecommerce, and entertainment. Founded in 2012 and headquartered in Redwood City, CA, Liftoff has a diverse, global presence.</div>
About the Revenue Engine team

The Revenue Engine team works to understand the fundamental economics of the mobile ad tech marketplace, including the elasticity of demand and the effects of competition. The team of machine learning engineers, software engineers, and data analysts develops theories, validates those theories with experiments and analyses, and uses the learnings to build production systems that improve outcomes for Liftoff and its advertisers.

As a Machine Learning Engineer on the Revenue Engine team, you will:
<ul>
<li>Build statistical models and production systems to balance advertiser performance with business goals.</li>
<li>Tune optimization parameters, measure internal competition, and model dynamic environments.</li>
<li>Design and run experiments to validate theories underpinning the mobile ad tech economy.</li>
<li>Develop applications in the areas of advertiser budget retention and growth, optimal margin allocation, and bidding innovations.</li>
<li>Collaborate with a team of world-class engineers with diverse backgrounds as well as peers across the broader company (e.g. Operations, GTM).</li>
<li>Use strong communication skills (verbal and written) to explain statistical and machine learning concepts to both technical and non-technical audiences.</li>
<li>Be part of an &quot;engineering excellence&quot; culture through state-of-the-art tools, risk-driven testing, explainable systems, and design/code review.</li>
</ul>
Requirements:
<ul>
<li>PhD in Computer Science, Machine Learning, Economics, or a related field.</li>
<li>Industry experience applying economics or machine learning to large scale problems.</li>
<li>Solid engineering and coding skills.</li>
<li>Excellent team communication and collaboration skills.</li>
<li>Experience with ad tech is a solid plus.</li>
</ul>
Location: 
This role is eligible for full-time remote work in one of our entities: CA, CO, ID, IL, FL, GA, MA, MI, MN, MO, NJ, NV, NY, OR, TX, UT, and WA.

We are a remote-first company with US hubs in Redwood City, Los Angeles, and New York City.

Travel Expectations: 
We offer several opportunities for in-person team gatherings, including but not limited to project meetings, regional meetups, and company-wide events. We expect our employees to attend these gatherings at least once per quarter. These gatherings provide essential opportunities for collaboration, communication, and team building.

#LI-EL1

#LI-REMOTE

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process, we provide Covey with job requirements and candidate-submitted applications. We began using Covey Scout for Inbound on January 22, 2024.

Please see the independent bias audit report covering our use of Covey here.<div>
Liftoff offers a fast-paced, collaborative, and innovative work environment where employees are empowered to grow and make an impact. We're shaping the future of the mobile app ecosystem&mdash;join us and help accelerate what's next. 


Liftoff's compensation strategy includes competitive salaries, equity, and benefits designed to support employee well-being and performance. We benchmark compensation based on role, level, and location to ensure fairness and market alignment. Benefits may include medical coverage, wellness stipends, and additional perks based on your country of residence. 


Liftoff is an equal opportunity employer. We are committed to creating an inclusive environment for all employees and applicants regardless of race, ethnicity, national origin, age, marital status, disability, sexual orientation, gender identity, religion, veteran status, or any other characteristic protected by applicable law.

Agency and Third Party Recruiter Notice:

Liftoff does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or Recruiting Team. All candidates must be submitted via our Applicant Tracking System by approved Liftoff vendors who have been expressly requested to make a submission by our Recruiting Team for a specific job opening. No placement fees will be paid to any firm unless such a request has been made by the Liftoff Recruiting Team and such a candidate was submitted to the Liftoff Recruiting Team via our Applicant Tracking System.</div></div>

YO IT Consulting

<div>
 
 Engagement Type:
 
 Independent Contractor
 
 
 
 Work Mode:
 
 Fully Remote
 
 
 
 Contract Type:
 
 Project-Based (Short-Term, Extendable)
 
 
 
 Role Overview
 
 
 
 collaborating with a leading AI research lab to support the evaluation of advanced machine learning systems. We are seeking experienced machine learning engineers and researchers to contribute to the design of high-quality evaluation suites that measure AI performance on real-world machine learning engineering tasks. The work focuses on translating practical ML research and engineering workflows into structured benchmarks for frontier models. This is a project-based, remote opportunity suited for experts with hands-on ML research experience.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design and write detailed evaluation suites for machine learning engineering tasks
 </li>
 <li>
 Assess AI-generated solutions across areas such as model training, debugging, optimization, and experimentation
 
 
 </li>
 </ul>
 
 Ideal Qualifications
 
 
 
 <ul>
 <li>
 3+ years of experience in machine learning engineering or applied ML research
 </li>
 <li>
 Hands-on experience with model development, experimentation, and evaluation
 </li>
 <li>
 Background in ML research (industry lab or academic setting strongly preferred)
 </li>
 <li>
 Strong ability to reason about ML system design choices and tradeoffs
 </li>
 <li>
 Clear written communication and high attention to technical detail
 
 
 </li>
 </ul>
 We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.
 
 
 Contract and Payment Terms
 
 
 <ul>
 <li>
 You will be engaged as an independent contractor.
 </li>
 <li>
 This is a fully remote role that can be completed on your own schedule.
 </li>
 <li>
 Projects can be extended, shortened, or concluded early depending on needs and performance.
 </li>
 <li>
 Your work at will not involve access to confidential or proprietary information from any employer, client, or institution.
 </li>
 <li>
 Payments are weekly on Stripe or Wise based on services rendered.
 </li>
 </ul>
</div>

Machine Learning Engineer - Remote

Call For Referral

<div>
 
 
 Machine Learning Engineer
 
 
 
 
 Work Mode:
 
 
 Remote
 
 
 
 
 Compensation:
 
 
 $100&ndash;$120 per hour
 
 
 
 
 Work Type:
 
 
 Hourly, Independent
 
 
 
 
 Role Overview
 
 
 
 This role supports the evaluation of
 
 advanced machine learning systems
 
 in collaboration with
 
 leading AI research initiatives
 
 . It is intended for
 
 experienced machine learning engineers and researchers
 
 who can contribute to the development of
 
 high-quality evaluation suites
 
 that measure AI performance on
 
 real-world machine learning engineering tasks
 
 .
 
 
 The work focuses on translating
 
 practical ML research and engineering workflows
 
 into
 
 structured benchmarks
 
 for
 
 frontier models
 
 . This is a
 
 project-based, fully remote
 
 opportunity for professionals with
 
 strong hands-on ML research and engineering experience
 
 .
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 
 Design and develop
 
 detailed evaluation suites for machine learning engineering tasks
 </li>
 <li>
 
 Evaluate AI-generated solutions
 
 across model training, debugging, optimization, and experimentation workflows
 </li>
 <li>
 
 Analyze and document
 
 system behavior, performance characteristics, and limitations
 </li>
 <li>
 
 Contribute to the creation of benchmarks
 
 that reflect real-world ML engineering practices
 </li>
 <li>
 
 Maintain high standards
 
 of technical accuracy, clarity, and consistency in all deliverables
 </li>
 </ul>
 
 
 Qualifications
 
 
 <ul>
 <li>
 
 3+ years
 
 of experience in machine learning engineering or applied ML research
 </li>
 <li>
 
 Hands-on experience
 
 with model development, experimentation, and evaluation
 </li>
 <li>
 
 Background in ML research
 
 in an industry or academic setting (strongly preferred)
 </li>
 <li>
 
 Strong ability
 
 to reason about ML system design choices and technical trade-offs
 </li>
 <li>
 
 Excellent written communication skills
 
 and
 
 high attention to technical detail
 
 </li>
 </ul>
 
 
 Work &amp; Payment Details
 
 
 <ul>
 <li>
 You will operate as an
 
 independent professional
 
 </li>
 <li>
 This is a
 
 fully remote
 
 role with a
 
 flexible schedule
 
 </li>
 <li>
 Projects may be
 
 extended, shortened, or concluded
 
 based on needs and performance
 </li>
 <li>
 The work does
 
 not involve access to confidential or proprietary information
 
 from any employer, client, or institution
 </li>
 <li>
 
 Payments are made weekly
 
 via
 
 Stripe or Wise
 
 , based on services delivered
 </li>
 <li>
 Candidates requiring
 
 H1-B or STEM OPT
 
 sponsorship are
 
 not supported
 
 at this time
 </li>
 </ul>
 
 
 Application &amp; Onboarding Process
 
 
 <ul>
 <li>
 
 Upload your resume
 
 </li>
 <li>
 
 AI interview:
 
 A short
 
 15-minute
 
 conversational session to understand your background, experience, and interest in the role
 </li>
 <li>
 
 Follow-up communication
 
 within a few days with next steps and onboarding details
 </li>
 </ul>
 
 
</div>

Machine Learning Engineer (Remote)  $100 –$120/hr

Waymo

<div>
 Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver&mdash;The World's Most Experienced Driver&trade;&mdash;to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo&rsquo;s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
 
 
 The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the autonomously driving vehicle (ADV), i.e., the system that &ldquo;perceives&rdquo; the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware.
 
 
 In this hybrid role you will report to a Technical Lead Manager.
 
 
 
 You Will
 
 
 
 <ul>
 <li>
 Create foundation scale data sets and training recipes, develop methods and recipes for human and machine labeling of foundation scale data sets.
 </li>
 <li>
 Create methods and recipes for continuous data intake, selection and incremental updates of large models, develop methods for data mining and recipes for automated data collection/model update flywheels.
 </li>
 <li>
 Develop methods and recipes for evaluating real-world performance of models, and detecting regressions in model updates.
 </li>
 <li>
 Develop and maintain ground-truth free performance metrics.
 
 
 </li>
 </ul>
 
 You Have
 
 
 
 <ul>
 <li>
 Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
 </li>
 <li>
 3+ years experience in Machine Learning and/or Computer Vision
 </li>
 <li>
 Experience with Python
 </li>
 <li>
 Experience with ML frameworks like PyTorch or JAX
 
 
 </li>
 </ul>
 
 We Prefer
 
 
 
 <ul>
 <li>
 MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline
 </li>
 <li>
 Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI
 </li>
 <li>
 Experience with C++
 
 
 </li>
 </ul>
 The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
 
 
 Waymo employees are also eligible to participate in Waymo&rsquo;s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
 
 
 Salary Range
 
 
 $170,000&mdash;$216,000 USD
</div>

Machine Learning Engineer, Data & Systems

Handshake

<div>
 
 About Handshake
 
 
 
 Handshake is the career network for the AI economy. More than 20 million knowledge workers, 1,600 educational institutions, and 1 million employers &mdash; including 100% of the Fortune 50 &mdash; trust Handshake to power career discovery, hiring, and upskilling. From freelance AI training gigs to first internships to full-time careers and beyond, we connect talent with opportunity at every stage.
 
 
 This unique position in the ecosystem is driving exceptional growth &mdash; in 2025, we tripled ARR at scale.
 
 
 
 Why Join Handshake Now
 
 
 
 <ul>
 <li>
 Shape how careers evolve in the AI economy at global scale, with visible real-world impact
 </li>
 <li>
 Work directly with leading AI labs, Fortune 500 partners, and top educational institutions
 </li>
 <li>
 Help build a rapidly scaling business on a path toward multi-billion-dollar revenue
 
 
 </li>
 </ul>
 
 The Role
 
 
 
 As a
 
 AI/Machine Learning Engineering Intern
 
 , you will contribute to building intelligent product experiences that help students discover and secure opportunities. Your work will span search, recommendations, matching, and other discovery systems that power job exploration on Handshake.
 
 
 You will gain hands-on experience developing, evaluating, and deploying machine learning models in a production environment, learning how large-scale ML systems are designed, optimized, and maintained.
 
 
 This is a paid, full-time summer internship with two cohort options:
 
 
 <ul>
 <li>
 May 18 &ndash; August 7, 2026
 </li>
 <li>
 June 15 &ndash; September 4, 2026
 
 
 </li>
 </ul>
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Partner with senior engineers and data scientists to develop machine learning models that improve user experience
 </li>
 <li>
 Build Agentic pipelines/workflows to improve the Handshake student/employer user experience
 </li>
 <li>
 Contribute to experimentation, model evaluation, and performance monitoring
 </li>
 <li>
 Participate in technical discussions, brainstorming sessions, and team reviews
 </li>
 <li>
 Document methodologies and findings to support knowledge sharing and long-term system improvements
 
 
 </li>
 </ul>
 
 You Have
 
 
 
 
 Must Haves
 
 
 
 <ul>
 <li>
 Are currently pursuing a degree in Computer Science, Data Science, or a related field
 </li>
 <li>
 Have strong programming skills in Python and experience with ML frameworks such as PyTorch or TensorFlow
 </li>
 <li>
 Have exposure to software engineering best practices (version control, testing, code reviews)
 </li>
 <li>
 Have familiarity with data analysis techniques and experience with SQL
 </li>
 <li>
 Have strong problem-solving skills and the ability to work in a collaborative team environment
 </li>
 <li>
 Have strong communication skills and are able to explain technical concepts effectively
 
 
 </li>
 </ul>
 
 Bonus Points
 
 
 
 <ul>
 <li>
 Experience with cloud platforms such as AWS, Google Cloud, or Azure
 </li>
 <li>
 Experience with modern coding tools like Cursor/Claude code/Codex
 </li>
 <li>
 Prior internship or project experience in applied machine learning in domains such as NLP, search and recommendation systems
 
 
 </li>
 </ul>
 
 We Offer
 
 
 
 Handshake provides benefits that help you feel supported and thrive at work and in life.
 
 
 (The below benefits apply to US-based interns.)
 
 
 <ul>
 <li>
 💰 Competitive hourly compensation
 </li>
 <li>
 📚 Mentorship and hands-on learning from experienced ML engineers
 </li>
 <li>
 💻 5 days/week in-office experience
 </li>
 <li>
 🤝 Structured intern programming and team events
 
 
 </li>
 </ul>
 Explore our mission, values, and open roles at
 
 joinhandshake.com/careers
 
 .
 
 
</div>

AI/Machine Learning Engineer Intern

Glocomms

<div>
 
 
 Software Engineer, Data &amp; Machine Learning
 
 
 
 
 Location:
 
 Remote, United States
 
 
 
 Employment Type:
 
 Full-time
 
 
 
 Compensation:
 
 Starting at $110K
 
 
 
 
 
 We're looking for a Software Engineer, Data &amp; Machine Learning to join a growing engineering team focused on building intelligent, production-grade systems. This role is ideal for an engineer with hands-on experience applying machine learning and deep learning techniques to real-world problems, particularly in areas like computer vision and modern AI models.
 
 
 You'll work closely with other engineers and machine learning practitioners to design, train, and deploy models that operate at scale. This is a hands-on role with meaningful ownership over model development, experimentation, and integration into production systems.
 
 
 
 
 
 Key Responsibilities
 
 <ul>
 <li>
 Design, build, and optimize machine learning models for tasks such as image classification, object detection, or related vision problems
 </li>
 <li>
 Experiment with modern deep learning architectures, including convolutional models and transformer-based approaches
 </li>
 <li>
 Contribute to end-to-end ML workflows, from data preparation and training through evaluation and deployment
 </li>
 <li>
 Analyze large, complex datasets to improve model performance and reliability
 </li>
 <li>
 Write clean, well-documented, production-quality code and contribute to shared ML tooling and infrastructure
 </li>
 <li>
 Partner with cross-functional engineering teams to integrate models into live systems
 </li>
 <li>
 Stay current with emerging techniques in machine learning and applied AI
 </li>
 </ul>
 
 
 
 
 Qualifications
 
 <ul>
 <li>
 2-5 years of experience in Software Engineering, Machine Learning, or a related field
 </li>
 <li>
 Strong proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or similar
 </li>
 <li>
 Hands-on experience with deep learning models, particularly in computer vision
 </li>
 <li>
 Solid understanding of supervised learning, model evaluation, and core ML concepts
 </li>
 <li>
 Experience with version control and modern development workflows
 </li>
 <li>
 Ability to work effectively in a collaborative, remote-friendly environment
 </li>
 <li>
 Strong problem-solving skills and a curiosity-driven mindset
 </li>
 <li>
 
 Permanent work authorization in the United States is required
 
 </li>
 </ul>
 
 
 
 
 Nice to Have
 
 <ul>
 <li>
 Exposure to transformer-based models or multimodal systems (e.g., vision + language)
 </li>
 <li>
 Familiarity with cloud platforms and containerized environments
 </li>
 <li>
 Experience supporting or deploying models in production
 </li>
 <li>
 Background working with experimentation, model tracking, or reproducible ML pipelines
 </li>
 <li>
 Interest in applying ML techniques to high-impact, real-world use cases
 </li>
 </ul>
 
 Compensation &amp; Benefits
 
 <ul>
 <li>
 Base salary starting at $110K
 </li>
 <li>
 Equity participation
 </li>
 <li>
 Comprehensive benefits package
 </li>
 <li>
 Fully remote role within the United States
 </li>
 <li>
 Emphasis on ownership, technical growth, and modern engineering practices
 </li>
 </ul>
 
 
 
 
 Location Notes
 
 
 This role is fully remote, but candidates must be based in San Francisco, New York City area, Seattle, Miami, or Austin, TX. The company is building teams in selective talent hubs to maintain convenient access to in-person collaboration when needed and to reduce exposure to future return-to-office mandates.
 
 
 
 
 
 At this time, the employer is unable to provide visa sponsorship or support visa transfers. Candidates must already have permanent work authorization in place.
 
</div>

Data Scientist, Computer Vision

Explore 179+ Machine learning engineer in San Francisco United States this March. Find roles across top companies and apply now to boost your career.

179 machine learning engineer jobs In San Francisco United States

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer - Remote

Machine Learning Engineer (Remote) $100 –$120/hr

Machine Learning Engineer, Data & Systems

AI/Machine Learning Engineer Intern

Data Scientist, Computer Vision