software engineer

data engineer

machine learning engineer Jobs in San Francisco

machine learning engineer

ai engineer

data engineer - data engineering Jobs in San Francisco

data engineer - data engineering

artificial intelligence engineer

Charles Schwab

<div><h2 class="jobSectionHeader"><b>Your opportunity</b></h2><div><br>
At Schwab, your career is more than a job&mdash;it's an opportunity to impact the lives of millions. Innovation and creative problem solving thrive here, as we challenge conventional approaches and prioritize collaboration. We value in-person teamwork, so this role is based on-site at our San Francisco office.</div><div></div><div><br>
As part of Schwab&rsquo;s AI Strategy &amp; Transformation team (AI.x), you&rsquo;ll join the central hub for Artificial Intelligence across the company. AI.x brings together product, engineering, strategy, and risk specialists to set enterprise AI vision, invest in transformative opportunities, and accelerate delivery organization-wide. Our team builds the scalable core platform for AI and explores next-generation GenAI initiatives that redefine client experiences.</div><div></div><div><br>
We&rsquo;re seeking a Senior AI Engineer who will design and deliver cutting-edge GenAI applications, enhancing the client journey and driving tangible business value. You&rsquo;ll collaborate closely with architects, engineers, and business leaders to align solutions with Schwab&rsquo;s strategic goals, and mentor junior team members&mdash;cultivating best engineering practices and a culture of continuous learning.</div><div></div><div><br>
In this pivotal role, you&rsquo;ll not only advance technical standards and solve complex challenges, but also lead rapid iterations from concept to production. You will bring curiosity, creativity, and technical depth to help shape the next era of AI at Schwab, with a special emphasis on site reliability, monitoring, observability, and operations. You&rsquo;ll ensure that the systems you build are robust, reliable, and well-monitored, implementing best practices for observability and operational excellence to maintain high performance and uptime for mission-critical AI applications.</div><ul><li>
Design, build, and deliver GenAI applications that elevate client experience and generate business impact.</li><li>
Champion reliability, monitoring, observability, and operational best practices for AI systems and data pipelines.</li><li>
Collaborate with cross-functional teams to align solutions with enterprise strategy and technical standards.</li><li>
Mentor and coach junior engineers, fostering strong practices and continuous learning.</li><li>
Lead by example in solving complex technical challenges and driving rapid iteration from concept to deployment.</li><li>
Implement and maintain monitoring, alerting, and incident response frameworks to ensure system health and reliability.</li><li>
Advance engineering standards, focusing on operational excellence and quality across all deliverables.</li></ul><h2 class="jobSectionHeader"><b>
What you have</b></h2><div><b><br>
Required Qualifications</b></div><ul><li>
8+ years of software development experience, with 4+ years as a hands-on senior engineer in startups and/or large organizations.</li><li>
Bachelor&rsquo;s degree in Computer Science or related field.</li><li>
5+ years building complex products from scratch, running them in production, and ensuring operational reliability.</li><li>
3+ years building applications leveraging AI models for measurable business impact.</li><li>
3+ years developing applications and data pipelines interfacing with large datasets.</li><li>
3+ years working with containers and cloud-native applications, operationalizing them in the public cloud with infrastructure as code.</li></ul><div><b>
Preferred Qualifications</b></div><ul><li>
Strong computer science fundamentals and experience across the tech stack.</li><li>
Experience with proprietary or open-source LLMs (e.g., Gemini, Claude, OpenAI) and deploying LLM-powered applications to production.</li><li>
Commitment to quality&mdash;driving high standards and writing tests at all levels.</li><li>
Experience writing and running evaluations for quality and consistency in LLM-generated output.</li><li>
Strong written and verbal communication skills to clearly convey ideas and feedback.</li><li>
Mentoring junior engineers and supporting their technical growth through code reviews and guidance.</li><li>
Mindset of continuous learning and improvement.</li><li>
Ability to solve complex problems with ambiguous or incomplete data in distributed systems.</li><li>
Demonstrated business domain knowledge relevant to previous products.</li><li>
Curiosity about new technologies and processes, proactively sharing knowledge and seeking improvement.</li><li>
Experience with Python and front-end development preferred but not required.</li><li>
Master&rsquo;s or advanced degree in Computer Science or related field.</li></ul><div>
In addition to the salary range, this role is eligible for bonus or incentive opportunities.</div><div><h2 class="jobSectionHeader"><b><br>
What&rsquo;s in it for you</b></h2><p>
At Schwab, you&rsquo;re empowered to shape your future. We champion your growth through meaningful work, continuous learning, and a culture of trust and collaboration&mdash;so you can build the skills to make a lasting impact. Our Hybrid Work and Flexibility approach balances our ongoing commitment to workplace flexibility, serving our clients, and our strong belief in the value of being together in person on a regular basis.</p><p>
We offer a competitive benefits package that takes care of the whole you &ndash; both today and in the future:</p><ul><li>
401(k) with company match and Employee stock purchase plan</li><li>
Paid time for vacation, volunteering, and 28-day sabbatical after every 5 years of service for eligible positions</li><li>
Paid parental leave and family building benefits</li><li>
Tuition reimbursement</li><li>
Health, dental, and vision insurance</li></ul></div></div>

Sr. AI Engineer, AI.x

Kickmaker

<div><div>Kickmaker is a high-tech product design and industrialization agency.</div>
<div></div>
<div>We support our customers from prototype to production run in our main vertical markets (medical, new mobility, electrification, agrotech, robotics, IOT and consumer devices) and our cross-disciplinary skills (embedded AI, high-tech manufacturing automation, eco-design, industrial design and WEB 3.0 for the economy of functionality).</div>
<div></div>
<div>We're evolving with a real maker culture! Passion, excitement and kindness are the pillars of KICKMAKER. This team and community spirit has enabled us to shape a unique corporate culture. Our approach: to enable everyone to fulfill their potential by working on exciting projects, and to encourage autonomy and initiative.</div>
<div></div>
<div>Present in France, China and the United States, our community counts over 250 passionate kickers and keeps growing. It is in this context that we are looking to strengthen our team in Boston, Seattle and San Fransisco.</div><div></div><div><p><br>
Within Kickmaker, the employee will assume the role of AI engineer, with the following main responsibilities:</p>
<p>
Supporting the qualification of Kickmaker clients&rsquo; requirements, as well as ensuring proper technical follow-up and management of projects for the assigned scope. As an integral part of the project team, he/she collaborates with other technical experts and contributes to the successful completion of the project within the defined timeline and budget.</p>
<p><b>
General responsibilities related to the role:</b></p>
<ul>
<li>Analyze sensors for data acquisition (RGB, depth, LiDAR, pressure, and others)</li>
<li>Design and implement data processing architectures</li>
<li>Perform business and technical analysis of data to understand underlying phenomena</li>
<li>Generate real and/or synthetic datasets (using Blender or other tools)</li>
<li>Implement classical algorithms</li>
<li>Apply Deep Learning approaches, including the use of pre-trained networks or training custom models</li>
<li>Test and analyze Deep Learning models</li>
<li>Review scientific publications and identify potential opportunities</li>
<li>Improve robustness and optimize Deep Learning models (e.g., deployment on microcontrollers)</li>
</ul>
<p>More generally, the employee shall also ensure the development and maintenance of the company&rsquo;s brand image with its clients and ensure compliance with applicable procedures, both in the performance of their own duties and with regard to the employees under their supervision.</p>
<p>
The employee must remain aware of the responsibilities associated with the performance of their duties and may not claim to have been unaware of them under any circumstances.</p>
<p>
In carrying out the responsibilities described above, and more broadly in the performance of all activities within the Company, the employee shall be placed under the direct supervision of the Executive Management of Kickmaker.</p>
<ul>
<li><b>Location</b>: San Francisco, California, USA</li>
<li><b>Base Salary: </b>$155 000 to $180 000/ year</li>
<li><b>Experience Required: </b>5 years in a relevant field</li>
</ul></div><div><div><b>Your adventure at Kickmaker</b></div>
<div></div>
<div>At Kickmaker you&rsquo;ll work on <b>5&ndash;10 projects annually</b>, choosing from a wide range of industries : from robotics, medical devices, fitness tech, and automotive, to micro-mobility, beauty tech, sports exoskeletons, and AI-driven hardware.
</div><div>Your path evolves with your curiosity: we help you grow where your professional ambitions and personal passions meet, always connected to the latest tech breakthroughs.</div>
<div></div>
<div>We offer a <b>benefits package</b> designed to support you and your family while keeping costs low. This includes health and dental coverage, paid time off and 5 sick days for rest and renewal. You can also join our 401(k) plan to invest in your future.</div>
<div></div>
<div><b>Our Culture &amp; Spirit</b></div>
<div>Kickmaker is built by innovators, for innovators. Across our 7 offices we give you the tools to make your ideas happen.</div><br>
<div></div>
<div></div><div>Our vision is simple: <b>build a space where innovators can explore, experiment, and push boundaries together</b>.</div>
<div>If you&rsquo;re curious about our spirit and way of working (and you&rsquo;ve got a minute) check out this short video where <b>Leonardo da Vinci &ldquo;visits&rdquo; Kickmaker.</b>An image is worth a thousand words, and this one will give you the full vibe</div>
<div></div>
<div><b>If you&rsquo;ve ever looked at a product and thought, &ldquo;I could build this better,&rdquo; let&rsquo;s talk!</b></div>
</div>
<p>We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</p></div>

AI Engineer

Apple

<p>The people here at Apple don't just create products - they create the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it.<br>
<br>
Data Services provides Data Solutions across Apple is looking for a creative and motivated AI Engineer with excellent problem solving and interpersonal skills. We are seeking a hands-on AI Solutions Engineer with deep technical expertise in Artificial Intelligence and Generative AI who can design, prototype, and implement scalable, high-impact AI solutions. This role blends system architecture, rapid prototyping, and cross-functional execution to shape the next generation of intelligent products. We would love to hear from you if you're enthusiastic, highly motivated, and want to make an impact!<br>
<br>
<b>Description</b><br>
<br>
As a strategic and technical leader, you will partner closely with engineers, product managers, product designers, data scientists, and business stakeholders to identify high-value AI opportunities, translate them into scalable architectures, and ensure successful deployment into production environments. The ideal candidate is a proactive self-starter who excels in cross-functional collaboration to empower our Sales and Sales Finance organizations. In addition to deep technical expertise, this role demands exceptional communication and presentation skills. You&rsquo;ll need to translate complex AI concepts for senior leadership, cross-functional peers, and non-technical partners- ensuring clear alignment, strong collaboration, and high-impact delivery. It&rsquo;s a unique opportunity for someone who thrives in a fast-paced environment and takes full ownership of their work from idea to execution.&quot;,&quot;responsibilities&quot;:&quot;Design end-to-end AI solutions with clear business impact, from concept to deployment, with a strong focus on feasibility, scalability, and performance.<br>
<br>
Build prototypes to evaluate architecture and modeling approaches, working closely with engineering teams to transition concepts into robust systems.<br>
<br>
Guide architectural decisions across LLM applications, multimodal systems, and agentic frameworks.<br>
<br>
Assess and integrate open-source tools, orchestration frameworks, context management solutions, and vector databases.<br>
<br>
Collaborate with product and business teams to define KPIs and ensure alignment of AI initiatives with strategic goals.<br>
<br>
Stay on top of emerging trends in Generative AI, prompt engineering, and agent-based architectures.<br>
<br>
Define and advocate for best practices in model serving, integration patterns, and runtime efficiency-not just training ops.<br>
<br>
<b>Preferred Qualifications</b><br>
<br>
Experience leading zero-to-one initiatives for AI product development<br>
<br>
Familiarity with synthetic data generation, fine-tuning techniques, and performance optimization for large models<br>
<br>
Understanding of agent-based interaction patterns, multi-agent communication protocols (e.g., MCP, A2A), and AG-UI concepts<br>
<br>
Prior work in designing user-facing AI features or tools; familiarity with frontend integration is a plus<br>
<br>
Excellent communication skills with the ability to translate technical concepts into business terms<br>
<br>
Ph.D. in Computer Science, AI, or related field, or equivalent industry experience with demonstrated impact in real-world applications<br>
<br>
<b>Minimum Qualifications</b><br>
<br>
2+ years industry experience with a Master&rsquo;s in Computer Science, AI, or related field, or equivalent industry experience with demonstrated impact in real-world applications<br>
<br>
1+ years plus of experience building AI-powered systems with a strong fundamental grasp of architecture and deployment<br>
<br>
Experience designing and delivering NLP or LLM-based systems, with knowledge of multi-modal and agentic AI frameworks<br>
<br>
Proficiency with Python to use ML libraries (e.g., PyTorch, TensorFlow, Transformers), vector search engines (e.g., FAISS, Weaviate or similar) and vector databases (e.g., Milvus, Vespa, or similar)<br>
<br>
Experience developing cloud platforms solutions (e.g., AWS, GCP, or public cloud, etc.)<br>
<br>
Hands-on experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex or similar), containerization (Docker, Kubernetes or similar), and scalable APIs<br>
<br>
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 .<br>
<br>
<b>Pay &amp; Benefits</b><br>
<br>
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.<br>
<br>
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.<br>
<br>
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.</p>

AI Engineer, AI & Data Platforms (AiDP)

Sutter Health

We are so glad you are interested in joining Sutter Health!
<br><br>
<b>Organization:</b><br>
SHSO-Sutter Health System Office-Bay
<br><br>
<b>Position Overview:</b><br>
<b>****Please Note:</b> While this position is listed as hybrid, regular in-office attendance is required. Candidates should be prepared to commute to the San Francisco office on a consistent basis to support team collaboration and business needs.****
<br><br>
Responsible for leading the design, build, and maintain Sutter Health’s artificial intelligence (AI) and machine learning (ML) infrastructure, including end to end pipelines for ML and large language models (LLM) that support analytics, data science, and enterprise AI use cases. This includes how AI models and associated data are ingested, processed, trained, deployed, monitored, governed, and secured across cloud and on premises environments. Ensures that AI systems meet high standards of performance, reliability, and compliance, enabling the organization to safely and effectively integrate AI capabilities into clinical, operational, and strategic workflows.
<br><br>
Utilizing modern artificial intelligence operations (AIOps) and machine learning operations (MLOps) practices, leads the operationalization of models, maintenance of scalable AI services, monitoring of system behavior, and automation of deployment workflows. Works with structured and unstructured data, clinical data models, healthcare data standards, and modern cloud platforms. Develops and validates ML models, integrates researcher built or vendor provided algorithms, and contributes to AI platform architecture and tooling. Sets standards for high quality, secure, and well governed AI systems that support advanced analytics, automation, and intelligent applications.
<br><br>
<b>Job Description:</b><br>
<b>****Please Note:</b> While this position is listed as hybrid, regular in-office attendance is required. Candidates should be prepared to commute to the San Francisco office on a consistent basis to support team collaboration and business needs.****
<br><br>
<b>EDUCATION:</b><br>
<ul>
<li>Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or related field; or equivalent combination of education and experience.</li>
</ul>
<b>TYPICAL EXPERIENCE:</b><br>
<ul>
<li>5 years recent relevant experience</li>
</ul>
<b>PREFERRED EXPERIENCE:</b><br>
<ul>
<li>Advanced experience with Azure cloud services, including containerized model hosting, Azure ML, secure environment management, and cloud‑native deployment patterns.</li>
<li>Strong proficiency in MLOps / LLMOps practices, including CI/CD pipelines, automated testing, observability, model versioning, canary/AB rollouts, and drift monitoring.</li>
<li>Hands‑on expertise in building and operating AI/ML/LLM pipelines (ingestion → preprocessing → training → inference → monitoring), using Python, modern container frameworks, and orchestration systems.</li>
<li>Experience integrating researcher‑built or vendor‑provided ML/LLM models into production workflows, including API‑based embedding, performance tuning, and secure data handling.</li>
<li>Familiarity with healthcare data standards and environments, such as clinical data models, unstructured clinical text, and privacy/security expectations in regulated domains.</li>
</ul>
<b>SKILLS AND KNOWLEDGE:</b><br>
<ul>
<li>Relevant experience in AI/ML Engineering and LLM/MLOps</li>
<li>Experience building end to end AI/ML pipelines, including training, deployment, monitoring, and retraining loops.</li>
<li>Strong programming skills in Python and familiarity with modern ML/LLM frameworks and libraries.</li>
<li>Hands on experience with Azure, including services such as Fabric, Foundry, Container Apps, AKS, and Application Insights.</li>
<li>Experience implementing AIOps / MLOps / LLM Ops practices, including CI/CD pipelines, automated testing, observability, and versioned deployments.</li>
<li>Experience with GitOps principles using GitHub Actions or similar tools.</li>
<li>Understanding of healthcare data models, including Epic Clarity, FHIR, HL7, and Caboodle.</li>
<li>Ability to evaluate and integrate machine learning models into production systems and support model lifecycle management.</li>
<li>Strong debugging skills across distributed systems, containerized environments, and cloud platforms.</li>
<li>Ability to work in cross functional environments with clinicians, data scientists, architects, and engineering teams.</li>
<li>Ability to produce high quality documentation and communicate complex technical concepts to diverse stakeholders.</li>
<li>Detail oriented, organized, and effective at prioritizing multiple concurrent initiatives.</li>
<li>Familiarity with HIPAA, PHI/PII security requirements, and regulatory considerations for healthcare AI.</li>
</ul>
These Principal Accountabilities, Requirements and Qualifications are not exhaustive but are merely the most descriptive of the current job. Management reserves the right to revise the job description or require that other tasks be performed when the circumstances of the job change (for example, emergencies, staff changes, workload, or technical development).
<br><br>
<b>Job Shift:</b><br>
Days
<br><br>
<b>Schedule:</b><br>
Full Time
<br><br>
<b>Days of the Week:</b><br>
Monday - Friday
<br><br>
<b>Weekend Requirements:</b><br>
As Needed
<br><br>
<b>Benefits:</b><br>
Yes
<br><br>
<b>Unions:</b><br>
No
<br><br>
<b>Position Status:</b><br>
Exempt
<br><br>
<b>Weekly Hours:</b><br>
40
<br><br>
<b>Employee Status:</b><br>
Regular
<br>Sutter Health is an equal opportunity employerEOE/M/F/Disability/Veterans.
<br><br>
Pay Range is $168,958.40 to $270,337.60 / annual salary
<br>The compensation range may vary based on the geographic location where the position is filled. Total compensation considers multiple factors, including, but not limited to a candidate’s experience, education, skills, licensure, certifications, departmental equity, training, and organizational needs. Base pay is only one component of Sutter Health’s comprehensive total rewards program. Eligible positions also include a comprehensive benefits package.

Bain & Company

What Makes Us A Great Place To Work
<br><br>
We are proud to be consistently recognized as one of the world’s best places to work. We are currently the top ranked consulting firm on [1] Glassdoor’s Best Places to Work list and have earned the #1 spot a record seven times. Extraordinary teams are at the heart of our business strategy, but these don’t happen by chance. They require intentional focus on bringing together a broad set of backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive work environment. We hire people with exceptional talent and create an environment in which every individual can thrive professionally and personally.
<br><br>
About Bain AI, Insights & Solutions (AIS)
<br><br>
Bain’s [2] AI, Insights & Solutions (AIS) team works with clients to design and deliver AI-powered solutions that create measurable business impact. You’ll operate in multidisciplinary teams alongside Bain consultants, other experts in product, design, architecture and engineering, and client stakeholders, translating ambiguous business problems into robust AI applications that can be piloted, scaled, and adopted.
<br><br>
The Impact You’ll Have
<br><br>
Bain works with clients on board-level and executive priorities, helping deliver step-change results across growth, productivity, and resilience. In that context, AI is rarely a point solution. The most meaningful outcomes come from building AI as part of an integrated system that combines technology with redesigned processes, operating model changes, and adoption at scale across the organization.
<br><br>
As an ML-AI Engineer Intern in AIS, you will build the technical core of these transformations and work as part of broader Bain consulting teams to move solutions from prototype to real adoption. The result is measurable impact at the company or enterprise level and, in many cases, helps clients set new performance standards for their industries.
<br><br>
The Role
<br><br>
We are hiring an ML-AI Engineer Intern to help build GenAI and agentic AI applications for enterprise use cases, ranging from rapid proofs of concept (POCs) to MVPs and, where appropriate, scaled production deployments. You will design and implement LLM-driven applications and agentic workflows that use tools, data, and enterprise systems to execute multi-step tasks reliably and safely.
<br><br>
While GenAI and agentic AI are the primary focus, you will also draw on data science and ML engineering skills as needed, including building evaluation approaches, working with data pipelines, and developing or integrating ML models when they materially improve performance or reliability.
<br><br>
You will have opportunities to work with major AI ecosystem partners through Bain’s partnerships, collaborating on real client deployments and helping shape how emerging capabilities are applied in enterprise settings.
<br><br>
Bain offers significant learning and growth opportunities through the breadth and depth of problems we solve, the level of impact we help clients achieve, and our apprenticeship model. You will learn by doing, with support from experienced teammates, frequent feedback, and increasing responsibility over time.
<br><br>
What You’ll Do
<br><br>
Build AI applications that drive real business outcomes
<br><ul>
<li>Contribute to the design and development of GenAI applications (e.g., copilots, workflow automation, decision support) using modern LLM stacks.</li>
<li>Support the implementation of agentic workflows where they add clear value (e.g., tool use, multi-step execution, human-in-the-loop controls), with attention to reliability, safety, and clear failure modes.</li>
<li>Assist in building robust agent capabilities including context engineering, memory/state management (short-term and long-term), orchestration, routing, and tool integration patterns.</li>
</ul>
Build and apply data science and machine learning capabilities
<br><ul>
<li>Contribute to ML solutions end-to-end: data preparation, feature engineering, model selection, training, validation/testing, and performance analysis.</li>
<li>Apply appropriate ML methods for the problem, spanning classical ML and deep learning (including sequence, text, and image models when relevant).</li>
<li>Develop working knowledge of modern deep learning concepts, including transformer fundamentals and LLM pre-training vs post-training concepts (e.g., instruction tuning, preference optimization).</li>
</ul>
<b>Engineer for real delivery:</b> POC → MVP → production
<br><ul>
<li>Write clean, testable, maintainable code and ship AI services through the full SDLC: build → test → deploy → monitor → iterate.</li>
<li>Support implementation of MLOps and GenAIOps practices: CI/CD, reproducibility, environment parity, model/prompt/agent versioning, and operational readiness.</li>
<li>Contribute to evaluation and observability for GenAI and agentic systems: tracing and instrumentation, regression test suites, automated scoring where appropriate, and iteration loops for prompt/policy optimization.</li>
<li>Gain exposure to secure enterprise deployment practices, including access controls, auditability, data handling for sensitive/PII data, and responsible AI guardrails.</li>
<li>Contribute to reusable components and accelerators (templates, evaluation harnesses, connectors, orchestration patterns) that scale across client contexts.</li>
</ul>
Thrive in a consulting environment
<br><ul>
<li>Communicate clearly with technical and non-technical audiences; present in working sessions, share recommendations, and help write crisp technical documentation.</li>
<li>Support client discussions, demos, and documentation development as part of broader engagement teams.</li>
</ul>
What We’re Looking For (Qualifications)
<br><br>
Educational background
<br><ul>
<li>Currently pursuing or recently completed a bachelor’s, master’s, or PhD in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Engineering, or a related quantitative field; or equivalent early-career industry experience.</li>
<li>Strong academic performance or demonstrated excellence through research, projects, internships, competitions, or open-source contributions.</li>
</ul>
Core engineering + AI application skills
<br><ul>
<li>0-2+ years of professional AI / ML engineering experience or equivalent experience through internships, research, academic projects, or industry roles, with strong backend engineering fundamentals.</li>
<li>Proficiency in Python and some experience building APIs/services (e.g., REST/gRPC) or comparable project-based experience.</li>
<li>Hands-on experience (academic, internship, or industry) building ML or LLM-powered applications, preferably with exposure to delivery considerations such as latency, cost, reliability, or security.</li>
<li>Exposure to retrieval/search systems (e.g., hybrid retrieval, vector search, reranking), and familiarity working with structured and unstructured data stores.</li>
<li>Exposure to agentic patterns (context management, tool integration, orchestration, memory/state handling); hands-on experience (academic, internship, or industry) preferred.</li>
<li>Strong engineering practices: testing, code review, version control, CI/CD, and performance profiling.</li>
</ul>
Breadth of knowledge across data science and machine learning
<br><ul>
<li>Experience training, validating, and testing ML models; strong understanding of overfitting, generalization, and evaluation methodology.</li>
<li>Practical experience with feature engineering and data preprocessing.</li>
<li>Familiarity with a broad set of ML algorithms (classical ML and deep learning), and the ability to choose methods that match constraints.</li>
</ul>
Delivery mindset and consulting skills
<br><ul>
<li>Excellent interpersonal and communication skills, able to explain technical decisions, tradeoffs, and results to mixed audiences.</li>
<li>Interest in applying AI to solve real-world business problems in a client-facing environment.</li>
</ul>
Working Model & Travel
<br><ul>
<li>This role requires a minimum of three days per week working together in person, either at a client location or at your Bain home office.</li>
<li>Travel may be required beyond your home office / primary working location. Frequency and destination vary by project needs.</li>
</ul>
U.S. Compensation Information
<br><br>
For all locations, the good-faith reasonable annualized full-time compensation for this role is commensurate with competitive geographic market rates. Additionally, in some locations compensation may vary based on several factors including, but not limited to relevant experience, education, licensure/certifications, training and skill level.
<br><br>
Compensation for this role in the United States includes a monthly base salary of $9,000 and Bain's best-in-class benefits package (details listed below).
<br><br>
<ul>
<li>Bain & Company's comprehensive benefits and wellness program is designed to help employees achieve personal independence, protection and stability in the areas most important to you and your family.</li>
<li>Bain pays 100% individual employee premiums for medical, dental and vision programs, offering one of the most comprehensive medical plans for employees without impacting your paycheck</li>
</ul>
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
<br>References
<br><br>
Visible links
<br>1. https://www.bain.com/about/awards-recognition/
<br>2. https://www.bain.com/careers/work-with-us/integrated-teams/ai-insights-solutions-ais/

ML-AI Engineering Intern

Baselayer

<div>
 <p>
  <strong>
   About Baselayer:
  </strong>
 </p>
 <p>
  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;
 </p>
 <p>
  &nbsp;
 </p>
 <p>
  <strong>
   About You:
  </strong>
 </p>
 <p>
  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.
 </p>
 <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>
 <p>
  <strong>
   Responsibilities:
  </strong>
 </p>
 <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>
 <p>
  &nbsp;
 </p>
 <p>
  <strong>
   Work Location
  </strong>
 </p>
 <ul>
  <li>
   Hybrid in SF. In office 3 days/week
  </li>
 </ul>
 <p>
  &nbsp;
 </p>
 <p>
  &nbsp;
 </p>
 <p>
  <strong>
   Compensation and Benefits
  </strong>
 </p>
 <ul>
  <li>
   <p>
    Salary range of $145,000 to $225,000
   </p>
  </li>
  <li>
   <p>
    Equity package
   </p>
  </li>
  <li>
   <p>
    Unlimited vacation
   </p>
  </li>
  <li>
   <p>
    Fully paid health insurance, dental, and vision
   </p>
  </li>
  <li>
   <p>
    401(k) with company match
   </p>
  </li>
 </ul>
 <p>
  &nbsp;
 </p>
</div>


Machine Learning Engineer

OpenAI

<div>
 We&rsquo;re building the next generation of OpenAI&rsquo;s internal developer experience, whether they&rsquo;re working human-only, agent-only, or fully hybrid. As AI changes how software gets written, reviewed, tested, and shipped, we are reimagining the best practices in the software development lifecycle, and integrating our dev infra and tooling into a seamless yet powerful offering.
 <br/>
 <br/>
 This role lives at the intersection of product design, engineering craft, and real-world scale. We&rsquo;re looking for a
 <strong>
  product-minded engineer
 </strong>
 who can own end-to-end experiences across multiple UI/UX surfaces across our internal tooling ecosystem, with a strong taste for interaction design and a keen eye for developer&rsquo;s needs.
 <br/>
 <br/>
 <strong>
  In This Role, You Will
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Own major product areas end-to-end: problem discovery, UX iteration, technical design, implementation, rollout, and ongoing improvements.
  </li>
  <li>
   Partner closely with engineers and internal stakeholders to understand pain points and translate them into simple, effective UI/UX for core developer workflows.
  </li>
  <li>
   Integrate and iterate on AI-empowered DevEx that balances capability vs simplicity/control.
  </li>
  <li>
   Set a high bar for performance, reliability, and usability, providing a world-class product experience for every engineer at OpenAI.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  You might thrive in this role if you
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Have 5+ years of professional engineering experience (excluding internships) building user-facing products.
  </li>
  <li>
   Are a strong frontend engineer or a full-stack engineer with deep UI instincts, and modern web fundamentals (TypeScript, React, component design, state management).
  </li>
  <li>
   Have built products in zero-to-one environments, or owned a product surface with ambiguous requirements and high urgency.
  </li>
  <li>
   Have experience building internal tools, enterprise tools, or workflow-heavy products for technical users.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About OpenAI
  <br/>
  <br/>
 </strong>
 OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 <br/>
 <br/>
 We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 <br/>
 <br/>
 For additional information, please see OpenAI&rsquo;s Affirmative Action and Equal Employment Opportunity Policy Statement.
 <br/>
 <br/>
 Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 <br/>
 <br/>
 To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
 <br/>
 <br/>
 We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
 <br/>
 <br/>
 OpenAI Global Applicant Privacy Policy
 <br/>
 <br/>
 At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
 <br/>
 <br/>
 Compensation Range: $185K - $490K
</div>


Software Engineer, Full-Stack — Developer Experience

Explore 202+ Artificial intelligence engineer in San Francisco this March. Find roles across top companies and apply now to boost your career.

202 artificial intelligence engineer jobs In San Francisco

Sr. AI Engineer, AI.x

AI Engineer

AI Engineer, AI & Data Platforms (AiDP)

AI Engineer

ML-AI Engineering Intern

Machine Learning Engineer

Software Engineer, Full-Stack — Developer Experience