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machine learning engineer Jobs in San Francisco

machine learning engineer

2026 future talent program - discovery biologics - intern Jobs in San Francisco

2026 phd scientist intern (competitive intelligence) Jobs in San Francisco

ai/ml engineer

machine learning intern

Uber

<div>We're looking for PhD candidates to work with the Competitive Intelligence Team as a Scientist intern during summer 2026 (12 weeks). As an intern, you will be embedded in a product team working on solving real-world Uber problems under the supervision of an analyst on that team, and will have the opportunity to partner closely with Scientists, Software Engineers, Product Managers, and other cross-functional partners.
 
 
About the Role
 
 
The Competitive Intelligence team works to understand the strategy and performance of Uber and other companies with similar products through a combination of external and internal data. Uber operates in a diverse array of markets and product categories filled with rapidly evolving competing options; assessing the success or failure of a product or strategy depends on understanding this context. Doing this, and doing it well, is an interesting and challenging problem. The team uses its data analysis, statistical modeling, economics, and business expertise to build scalable data products and ship actionable insights.
 
 
We are looking for candidates passionate about solving new and difficult problems with data. You will build out and own competitive metrics/models, provide key insights, conduct deep dive analysis to understand new opportunities and empower teams to make more informed business and strategy decisions with competitive intelligence.
 
 
What You'll Do
<ul><li>Work with a mentor closely to define a business problem, scope a project, develop, and prototype the solution using data-driven approaches
</li><li>Work with engineers and product managers to turn prototypes into scalable solutions
</li><li>Present findings to leaders to inform decisions
</li><li>Establish standard methodologies for science such as modeling, coding, analytics, optimization, and experimentation
</li></ul>Basic Qualifications
<ul><li>Pursuing a Ph.D. majoring in Statistics, Machine Learning, Economics, or other related quantitative fields
</li><li>Candidates should have at least one semester/quarter left of their education after finishing the internship
</li><li>Strong problem-solving and analytical abilities
</li></ul>Preferred Qualifications
<ul><li>Coding proficiency in areas such as R, Spark, SQL, Python
</li><li>Background in data visualization via open-source libraries/packages or third-party tools (i.e. Tableau, Mixpanel, Looker, or similar)
</li><li>Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, stochastic processes, economics, and analytics
</li><li>Experience in the following areas: Exploratory Data Analysis, Statistical Analysis, ML Model Development, Competitive Intelligence, Causal Inference, Operations Management, Transportation
</li><li>0-2 years of prior work experience in an analytical setting
</li><li>Organized, detail-oriented and able to work independently on multiple projects at once
</li><li>Ability to communicate effectively with both technical and business partners
</li><li>Open to feedback, excellent at implementing newly learned ideas and concepts
</li><li>Research mentality with a bias towards action to structure a project from idea to prototype to implementation
</li>Independence, self-starter mindset, excellent communication, and outstanding follow-through - you energetically tackle your work and love the responsibility of being individually empowered 
<li>
</li></ul> 
 
For San Francisco, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For Seattle, WA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For Sunnyvale, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For all US locations, you will also be eligible for various benefits.</div>

2026 PhD Scientist Intern (Competitive Intelligence)

Research Scientist Intern, FAIR Chemistry

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

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

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>

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Application deadline: Applications will be accepted on an ongoing basis 
 
This opportunity is for U.S. citizens who have served in the U.S. Armed Forces including Reserves, National Guard, and service member spouses.
 
 
<ul><li>Please list your service in your resume to be considered for this position.</li></ul> 
Do you want to solve real customer problems through innovative technology? Do you enjoy working on scalable services in a collaborative team environment? Do you want to see your code directly impact millions of customers worldwide? 
 
At Amazon, we hire the best minds in technology to innovate and build on behalf of our customers. Customer obsession is part of our company DNA, which has made us one of the world's most beloved brands. 
 
Our SDE interns use modern technology to solve complex problems while seeing their work's impact first-hand. The challenges SDE interns solve at Amazon are meaningful and influence millions of customers, sellers, and products globally. We seek individuals passionate about creating new products, features, and services while managing ambiguity in an environment where development cycles are measured in weeks, not years.
 
 
At Amazon, we believe in ownership at every level. As a SDE intern, you'll own the entire lifecycle of your code - from design through deployment and ongoing operations. This ownership mindset, combined with our commitment to operational excellence, ensures we deliver the highest quality solutions for our customers. 
 
We're looking for curious minds who think big and want to define tomorrow's technology. At Amazon, you'll grow into the high-impact engineer you know you can be, supported by a culture of learning and mentorship. Every day brings exciting new challenges and opportunities for personal growth. 
 
Amazon internships across all seasons are full-time positions, and interns should expect to work in office, Monday-Friday, up to 40 hours per week typically between 8am-5pm. Specific team norms around working hours will be communicated by your manager. Interns should not have conflicts such as classes or other employment during the Amazon work-day. Applicants should have a minimum of one quarter/semester/trimester remaining in their studies after their internship concludes. 
 
We will take your location preferences into consideration. Preferences are based on business availability and are not guaranteed. Applicants will be considered at all locations we host interns in the United States including but not limited to:
 
 
<ul><li>CA (Culver City, San Francisco, Santa Clara, Sunnyvale)
</li><li>CO (Denver)
</li><li>MA (Boston)
</li><li>NJ (Jersey City)
</li><li>NY (New York)
</li><li>VA (Arlington)
</li><li>WA (Bellevue, Seattle, Redmond)
</li></ul>***Locations are subject to change*** 
 
During your application, you will have the opportunity to highlight your expertise in one or more of these specialized areas: 
 
&bull; Machine Learning &bull; Distributed Systems and Data Management &bull; Database Systems &bull; Quantum Computing &bull; Network Development &bull; Query Processing and Optimization &bull; Automated Reasoning &bull; Embedded Systems &bull; Data Engineering &bull; Mobile Development &bull; Game Development 
 
While team placement is based on business needs, sharing your specific skills and interests helps us better align your experience with potential roles. 
 
Key job responsibilities 
<ul><li>Collaborate and communicate effectively with experienced cross-disciplinary Amazonians to design, build, and operate innovative products and services that delight our customers, while participating in technical discussions to drive solutions forward.</li><li>Design and develop scalable solutions using cloud-native architectures and microservices in a large distributed computing environment.</li><li>Participate in code reviews and contribute to technical documentation.</li><li>Build and maintain resilient distributed systems that are scalable, fault-tolerant, and cost-effective.</li><li>Leverage and contribute to the development of GenAI and AI-powered tools to enhance development productivity while staying current with emerging technologies.
</li><li>Write clean, maintainable code following best practices and design patterns.</li><li>Work in an agile environment practicing CI/CD principles while participating in operational responsibilities.</li><li>Demonstrate operational excellence through monitoring, troubleshooting, and resolving production issues.</li></ul> 
A day in the life 
As an intern, you will be matched to a manager and a mentor and will have the opportunity to influence the evolution of Amazon technology and lead critical projects early in your career.
 
 
In addition to working on an impactful project, you will have the opportunity to engage with Amazonians for both personal and professional development, expand your network, and participate in activities with other interns throughout your internship. No matter the location of your internship, we give you the tools to own your project and learn in a real-world setting.</div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>Are enrolled in a Bachelor's degree or above in Computer Science, Computer Engineering, Data Science, Information Systems, or related STEM fields</li><li>Expected conferral date between October 2026 &ndash; September 2029</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with at least one general-purpose programming language such as Java, Python, C++, C#, Go, Rust, or TypeScript</li><li>Experience with data structure implementation, basic algorithm development, and/or object-oriented design principles</li><li>Experience from previous technical internship(s) or demonstrated project experience</li><li>Demonstrated ability to learn and adapt to new technologies quickly</li><li>Basic understanding of software development lifecycle (SDLC)</li><li>Strong problem-solving and analytical skills</li><li>Excellent written and verbal communication skills</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The starting pay for this position is listed below. Final starting pay will be based on factors including experience, qualifications, and location. Starting Day 1 of employment, Amazon offers EAP, Mental Health Support, Medical Advice Line, 401(k) matching. Learn more about our benefits at https://hiring.amazon.com/why-amazon/benefits. 
USA, CA, SAN FRANCISCO - 127,100.00 - 185,000.00 USD annually 
USA, CA, San Francisco - 127,100.00 - 185,000.00 USD annually 
USA, CA, Santa Clara - 122,600.00 - 170,000.00 USD annually 
USA, CA, Santa Clara - 127,100.00 - 185,000.00 USD annually 
USA, CO, DENVER - 110,500.00 - 160,000.00 USD annually 
USA, CO, Denver - 110,500.00 - 160,000.00 USD annually 
USA, MA, BOSTON - 110,500.00 - 160,000.00 USD annually 
USA, MA, Boston - 110,500.00 - 160,000.00 USD annually 
USA, NJ, Jersey City - 121,600.00 - 180,600.00 USD annually 
USA, NY, BROOKLYN - 121,600.00 - 180,600.00 USD annually 
USA, NY, Carle Place - 121,600.00 - 180,600.00 USD annually 
USA, NY, New York - 121,600.00 - 180,600.00 USD annually 
USA, VA, ARLINGTON - 110,500.00 - 160,000.00 USD annually 
USA, VA, Arlington - 110,500.00 - 160,000.00 USD annually 
USA, WA, Seattle - 110,500.00 - 160,000.00 USD annually</div>

Software Development Engineer Internship - Military Veteran

<div>Site Name: Cambridge 300 Technology Square, London The Stanley Building, South San Francisco 611 Gateway Blvd 
Posted Date: Mar 2 2026 
At GSK we see a world in which advanced applications of Machine Learning and AI will allow us to develop transformational medicines using the power of genetics, functional genomics and machine learning. AI will also play a role in how we diagnose and use medicines to enable everyone to do more feel better and live longer. It is an ambitious vision that will require the development of products at the cutting edge of Machine Learning and AI.
The opportunities for machine learning extend to many other areas of our business, including medicine safety, manufacturing, and supply chain. To realize these opportunities, GSK has created a global Artificial Intelligence and Machine learning group (AI/ML), with locations in London, San Francisco, Boston, Philadelphia, and Heidelberg, to focus on the development and application of machine learning to problems of critical importance at GSK. We possess a world-leading data and computational environment (including specialist hardware) to enable large-scale, scientific experiments that exploit GSK&rsquo;s unique access to data.
By actively engaging with the machine learning community and publishing our research, code and models built on public data, the AI/ML group operates at the cutting-edge of machine learning research. To help us, we seek a passionate researcher who wishes to turn their talents to the application of causal machine learning to the healthcare sector. You will be working with multiple Research Engineers on building products to support multiple large-scale projects within AI/ML. In addition, the researcher will learn about the pharmaceutical industry and software engineering and translate their research into tools that aid discovery and development of transformational medicines and vaccines. You will have access to outstanding experts in biology, clinical and translational research, chemistry, (software) engineering, data science and machine learning; unrivalled data sources and GSK&rsquo;s state-of-the-art laboratory and compute infrastructure to help you develop and validate your machine learning research.
As a Machine Learning Engineer focusing on applications in oncology, you will be expected to:<ul><li>
Design and implement novel scientific approaches for biophysical modeling and foundation model-driven analysis of multi-modal clinical and genomic data for biomarker and target discovery to improve patient selection and enable next-generation assets.</li><li>
Design, develop, and implement analytical solutions using a variety of commercial and open-source tools (common tools include PyTorch and scikit-learn). &bull; Connect and collaborate with subject matter experts in biology, genomics, and medicine.</li><li>
Identify opportunities to apply the latest advancements in Machine Learning and Artificial Intelligence to build, test, and validate predictive models.</li><li>
Develop and embed automated and agentic processes for predictive model validation, deployment, and implementation.</li><li>
Deploy your algorithms to production to identify actionable insights from large databases.</li></ul><h1 class="jobSectionHeader">
Why you?
</h1>Basic Qualifications:
We are looking for professionals with these required skills to achieve our goals:<ul><li>
Master&rsquo;s degree in computer science, applied math, statistics, physics, systems biology, computational biology, bioinformatics, or related field</li><li>
Experience in Python programming and knowledge in machine learning, statistics, and applied math.</li><li>
Familiarity with modern machine learning methods (generative models, representation learning)</li><li>
Experience in building deep learning models, preferably with exposure to biophysical modeling, functional genomics, molecular and cellular biology or to modeling dynamical systems</li><li>
Experience with at least one Deep Learning framework such as PyTorch</li></ul>
Preferred Qualifications:
If you have the following characteristics, they would be a plus:<ul><li>
PhD in computer science, applied mathematics, statistics, physics, systems biology, computational biology, bioinformatics, or a related field.</li><li>
Experience in analyzing real-world and/or clinical data.</li><li>
Experience in incorporating agentic models into ML workflows</li><li>
Understanding of best practices in software engineering, including training and operating algorithms at scale, and production deployment of ML services.</li><li>
Knowledge of cancer biology and precision oncology.</li><li>
Excellent written and verbal communication skills.</li><li>
Ability to digest, synthesize, and implement innovative methods from scientific literature.</li><li>
Ability to solve complex problems using creative approaches, state-of-the-art tools, and best engineering practices.</li><li>
Ability to work autonomously and collaboratively as part of a team, both teaching and learning every day.</li><li>
High impact publications at venues such as NeurIPS, ICML, ICLR etc. would be a plus</li><li>
Publicaiton in natural sciences would be a plus</li></ul>
#LI-GSK
# GSKAIML<ul><li>If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $136,125 to $226,875.
</li></ul> 
The US salary ranges take into account a number of factors including work location within the US market, the candidate&rsquo;s skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave. 
 
If salary ranges are not displayed in the job posting for a specific country, the relevant compensation will be discussed during the recruitment process.
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
Why GSK?
Uniting science, technology and talent to get ahead of disease together.
GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases &ndash; to impact health at scale.
People and patients around the world count on the medicines and vaccines we make, so we&rsquo;re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.
Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us at HR.AmericasSC-CS@gsk.com where you can also request a call.
Please note should your inquiry not relate to adjustments, we will not be able to support you through these channels. However, we have created a Recruitment FAQ guide. Click the link where you will find answers to multiple questions we receive
GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.
Important notice to Employment businesses/ Agencies
GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK. GSK shall therefore not be liable for any fees arising from such actions or any fees arising from any referrals by employment businesses/agencies in respect of the vacancies posted on this site.
Please note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenses GSK incurs, on your behalf, in the event you are afforded an interview for employment. This capture of applicable transfers of value is necessary to ensure GSK&rsquo;s compliance to all federal and state US Transparency requirements. For more information, please visit the Centers for Medicare and Medicaid Services (CMS) website at https://openpaymentsdata.cms.gov/</div>

AI/ML Engineer

Explore 97+ Machine learning intern in San Francisco this March. Find roles across top companies and apply now to boost your career.

97 machine learning intern jobs In San Francisco

2026 PhD Scientist Intern (Competitive Intelligence)

Research Scientist Intern, FAIR Chemistry

Machine Learning Engineer

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

Machine Learning Engineer

Software Development Engineer Internship - Military Veteran

AI/ML Engineer