San Francisco, CA

Engineer Jobs in San Francisco, CA

96 jobs found

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Today

Machine Learning Engineer

Watney San Francisco, CA

San Francisco, CA

Today

Full time Artificial Intelligence Data Processing Data Science

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Job Description

In this Machine Learning Engineer position at Watney, you will help improve models by working directly from a live fleet of robots, using real-world video and data to drive training experiments and measure next-deployment performance.

About the Role

At Watney, machine learning engineers convert outputs from an operational robot fleet into better models. The fleet generates substantial video from real work in the field, and turning that material into models that perform better on the next deployment is a core challenge. Model development spans multiple task types, including what the robot perceives, how it decides, and how it acts.

Your work will support the roadmap from imitation learning toward broader generalization. This includes running training experiments, curating and labeling the data that powers them, and evaluating which approaches translate successfully to performance on the robot fleet.

Responsibilities

Run and evaluate training experiments as models scale.
Curate and clean the data used to train models.
Contribute to how new data is labeled and structured.
Track the metrics that distinguish models that help from models that do not.
Partner with Teleoperations to understand and improve data at its source.

Requirements

Experience training models on real-world data pulled from actual operation.
Experience with imitation learning, reinforcement learning, or a similar method for control.
Ability to write production machine learning code in Python, PyTorch, or comparable tooling.
Comfort with cleaning and curating messy, real-world data.

Technologies

Python
PyTorch

Mission

Watney’s mission is to expand human ambition in the physical world.

Location

San Francisco, CA (onsite)

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Today

Sr Machine Learning Engineer

Uber San Francisco, CA

San Francisco, CA

Today

$202k - $224k/yr Full time Artificial Intelligence Big Data Data Analytics

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Job Description

Uber is hiring a Senior Machine Learning Engineer (onsite) in San Francisco to build and own machine learning models for membership offer relevance and messaging personalization across Uber and Uber Eats.

Responsibilities

Own end-to-end lifecycle for targeting and personalization models, including problem framing, data, training, offline evaluation, online experimentation, deployment, and monitoring.
Develop heterogeneous treatment effect models to estimate incremental impact of interventions on users.
Create budget-constrained allocation systems that convert per-user uplift predictions into offer decisions under real constraints, including incentive budget, variable contribution targets, cannibalization of full-price conversion, and per-surface frequency caps.
Build personalized ranking and sequencing models for membership messaging across Eats and Mobility apps, balancing conversion, user experience, and contention with non-member content.
Collaborate with backend and platform engineers to productionize models in real-time serving paths and batch pipelines, ensuring production behavior matches offline results.
Partner with Product, Engineering, Data Science, Finance, and Marketing to translate ambiguous business goals into concrete ML problem statements.

Requirements

Bachelor’s degree in Computer Science, Statistics, Economics, Operations Research, or a related quantitative field, or equivalent practical experience.
5+ years of experience building and shipping ML models that drive product or business decisions in production.
Proficiency in Python and modern ML frameworks, including PyTorch, scikit-learn, and XGBoost/LightGBM or equivalents.
Strong SQL skills and hands-on experience with large-scale data processing using Spark, Hive, Presto, or comparable tools.
Experience designing and analyzing experiments, including A/B testing, power analysis, variance reduction, and responsible interpretation of noisy results.
Experience delivering models across the full lifecycle, from notebooks to production pipelines, serving, monitoring, retraining, and deployment.
Ability to explain modeling decisions and associated business consequences clearly to both technical and non-technical audiences.

Technologies

Python
PyTorch
scikit-learn
XGBoost
LightGBM
SQL
Spark
Hive
Presto

Preferred Qualifications

Experience training deep feed-forward models (MLP) for uplift estimation.
Experience with constrained optimization for resource allocation, including LP/MIP, Lagrangian duality, dual-price, or bidding-style budget pacing.
Experience with incentive, promotion, pricing, or discount targeting at consumer scale.
Experience with contextual bandits or reinforcement learning for sequential decisioning.
Familiarity with subscription business metrics and modeling, including trial-to-paid conversion, retention curves, LTV modeling, cannibalization, and incrementality measurement.
Experience leading technical direction across an ambiguous, cross-functional scope.

Salary

USD 202,000 - 224,000 per year
For San Francisco, CA-based roles: base salary range is USD $202,000 per year - USD $224,000 per year

Benefits

Eligible to participate in Uber’s bonus program; may be offered an equity award and other types of compensation.
All full-time employees are eligible to participate in a 401(k) plan.
Eligibility for various benefits.

Work Location

San Francisco, CA (onsite)
Unless approved for full remote work, employees must spend at least 50% of their time in-office.
Some roles (including those at greenlight hubs) require full-time in-office presence.

Equal Opportunity

Uber considers qualified applicants for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.
Uber also considers applicants regardless of criminal histories, consistent with legal requirements.
Accommodation: if you have a disability or special need that requires accommodation, complete the accommodation form.

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Today

Senior Staff Software Engineer, Developer Productivity

Asana San Francisco, CA

San Francisco, CA

Today

$324k - $337k/yr Full time Senior Ai Developer Tooling Developer

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Job Description

Lead AI-driven improvements to Asana’s software development lifecycle as a Senior Staff Software Engineer in Developer Productivity.

Responsibilities

Drive developer productivity and AI developer tooling initiatives with impact across 500+ developers at Asana
Collaborate with the Developer Productivity Group Tech Lead to shape technical vision and strategy for 6+ engineering teams, focused on improving engineering velocity
Build and align the roadmap for Asana’s development platform to accelerate feedback loops across the development lifecycle
Improve how every Asana engineer ships through stronger tooling, frameworks, and infrastructure
Own outcomes related to extending internal tooling used to delegate work to agents across harnesses
Mentor senior and staff-level engineers in Developer Productivity and across Foundations and the wider Engineering organization
Serve as a technical resource for team-level tech leads on technical planning, design & architecture, and prioritizing tech debt

Requirements

10+ years experience as a technical contributor on large-scale products
2+ years owning a build system, developer environment, CI, or equivalent at an organization of 200+ engineers
Experience making and delegating technical decisions with org-wide impact
Fluency with current AI developer tooling, plus strong opinions to collaborate with teams and set direction
Passion for coaching and mentoring engineers across experience levels
Strong collaboration skills and a commitment to an inclusive culture where people can contribute fully
Curiosity about AI tools and emerging technologies, with willingness to learn and leverage them for productivity, collaboration, and decision-making

Compensation

USD 323,500 - 336,750 per year

Location

San Francisco, CA (hybrid)

Benefits

Mental health, wellness & fitness benefits
Career coaching & support
Inclusive family building benefits
Long-term savings or retirement plans
In-office culinary options to match dietary preferences

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Today

Technical Support Engineer

Novani LLC San Francisco, CA

San Francisco, CA

Today

$75k - $90k/yr Full time Active Directory End User Support Hardware Support

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Job Description

Novani LLC is hiring a Technical Support Engineer for an onsite, in-person role in San Francisco, CA. This position supports multiple clients and centers on resolving end user IT issues across a wide range of environments, including servers, desktops, laptops, mobile devices, VoIP, and wired and wireless networking. You’ll work alongside a team while handling problems with a focus on timely, professional service.

What you’ll do

Provide IT support across multiple clients, working both independently and with fellow team members
Troubleshoot and resolve end user issues in a timely and professional manner
Apply strong technical aptitude across servers, desktops, laptops, mobile devices, VoIP services, and wired and wireless network devices and configurations
Maintain clear client and peer communication to manage expectations effectively

What you bring

Minimum 2 years of progressive IT support experience in a help desk equivalent capacity
Proven knowledge of Windows and Mac OS X operating systems
Microsoft 365 and Active Directory administration and support experience
Strong understanding of networking concepts and technologies including TCP/IP, DHCP, VLAN, VPN, and related configurations
Experience with smartphone device configuration, management, and troubleshooting
Familiarity with GPOs, PowerShell, and scripting
Availability to work after hours and/or weekends
Ability to travel within the SF Bay Area
Excellent analytical skills plus verbal and written communication ability
Strong customer service orientation and enjoyment working with end users
A team mindset: willingness to learn and share knowledge

Tools and technologies you’ll work with

Windows, Mac OS X
Microsoft 365, Active Directory
TCP/IP, DHCP, VLAN, VPN
GPOs, PowerShell, scripting
VoIP

Benefits

401k with annual company contributions
Medical and Dental plans with the company paying 100% of base plans
Vision Care plan
Pre-Tax commuter benefits
Paid Time Off (vacation, sick, public holidays)
Training and development
401(k), Dental insurance, Health insurance, Paid time off, Vision insurance

Job type: Full-time
Work location: In person
Salary: $75,000 - $90,000 per year (commensurate with experience)

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1d ago

AI Engineer, AI.x

Charles Schwab San Francisco, CA

San Francisco, CA

1d ago

$79 - $96/hr Full time Ai Engineer Artificial Intelligence Generative Ai Applications

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Job Description

AI.x is Schwab’s AI Strategy & Transformation team, and this role focuses on delivering GenAI applications that improve client experience and create business value.

Responsibilities

Contribute to the design, development, and delivery of GenAI applications tied to client experience and business value
Partner with architects, engineers, and business leaders to ensure solutions align with Schwab’s enterprise strategy
Learn from senior engineers, participate in technical discussions, and help build engineering practices that support continuous learning
Take ownership of complex technical challenges, support best engineering standards, and drive iterations from concept through production
Apply curiosity and technical creativity to help shape the next generation of AI at Schwab

Requirements

3+ years of software development experience
1+ year hands-on engineering experience in startups and/or large organizations
Bachelor’s degree in Computer Science or related field
2+ years experience building products and supporting them in production environments
1+ year experience developing applications that use Artificial Intelligence (AI) models to deliver business impact
1+ year experience working with applications or data pipelines that interface with large datasets
1+ year experience with containers and cloud-native applications, including exposure to deploying to the public cloud using infrastructure as code

Technologies

Artificial Intelligence (AI) models
Containers
Cloud-native applications
Infrastructure as code
Public cloud

Preferred Qualifications

Strong computer science fundamentals and experience across multiple parts of the tech stack
Exposure to proprietary or open-source LLMs (Gemini, Claude, OpenAI or other models) and contributing to LLM-powered applications
Experience maintaining tests and maintaining quality standards
Experience evaluating and monitoring LLM-generated outputs for quality and consistency
Strong communication skills, including sharing perspectives verbally and in writing
Interest in mentoring peers and learning through feedback and code reviews
Demonstrated commitment to continuous learning and improvement
Ability to solve complex problems with ambiguous or incomplete data within distributed systems
Broad business domain knowledge relevant to products contributed to
Curiosity about new technologies and processes, with a preference for growing skills and sharing knowledge with the team
Experience with Python and front-end development is preferred, not required
Master’s or advanced degrees in Computer Science or related fields are a plus

Benefits

401(k) with company match and Employee stock purchase plan
Paid time for vacation, volunteering, and 28-day sabbatical after every 5 years of service for eligible positions
Paid parental leave and family building benefits
Tuition reimbursement
Health, dental, and vision insurance
Bonus or incentive opportunities

What’s in it for you

Hybrid Work and Flexibility approach balancing workplace flexibility with serving clients and regular in-person collaboration
Competitive benefits package supporting employees today and in the future

Eligible Schwabbies receive

Medical, dental and vision benefits
401(k) and employee stock purchase plans
Tuition reimbursement to continue developing your career
Paid parental leave and adoption/family building benefits
Sabbatical leave available after five years of employment

Location: San Francisco, CA (onsite)
Compensation: USD 79 - 96 per hourly
Experience: Minimum 3 years
Education: Bachelor’s degree in Computer Science or related field

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2d ago

Software Engineer 1, Platform

Sydecar San Francisco, CA

San Francisco, CA

2d ago

$136k - $155k/yr Full time Database Developer DevOps

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Job Description

Sydecar builds a strong foundation for engineering productivity, and the Platform Team is at the center of it. As a Software Engineer 1 on the Platform Team, you’ll help create internal paved roads that make it easier for engineers to ship safer, faster, and at scale. You’ll join a high-trust environment that emphasizes ownership, thoughtful execution, mentorship, and a sustainable pace.

Compensation range: $136,000 - $155,000 per year.

Location: San Francisco, CA (hybrid). Hybrid in San Francisco or New York City with two to three days per week in office.

What you’ll build

The Platform Team owns the shared foundations that improve developer productivity and delivery reliability. You’ll work on core services and infrastructure, release and test automation, and security capabilities that support the entire engineering organization.

Build and improve the internal developer platform, including CI/CD pipelines, build and deployment automation, and local and preview environments.
Create a “golden path” to help engineers ship quickly and safely.
Design, operate, and scale shared services and cloud infrastructure as code using Terraform, with reliability, observability, and cost efficiency.
Advance release automation and test automation so production deployments are routine and low-risk, including safe rollout patterns and easy rollbacks.
Strengthen the team’s security posture and help build a distributed security practice across the engineering org.
Partner with product teams as an enabler by defining standards and interfaces and co-building when teams share dependencies, while keeping the platform focused on general-purpose foundations.

How you’ll work

Contribute to work from concept through deployment, balancing speed with scalability.
Grow through pairing, code review, and mentorship from senior engineers, and participate in architecture discussions.
Collaborate across engineering, product, design, and operations.

What you bring

Strong computer science fundamentals (data structures, algorithms, systems). Degree in CS/related field or equivalent practical experience.
AI-native approach: comfort using agentic or AI-assisted development tools as part of everyday workflow.
Curiosity, fast learning, and ownership, including the ability to figure things out.
Clear communication and strong collaboration skills.
0–2 years of professional experience (internships, co-ops, and substantial personal or academic projects count).

Tech stack you’ll work with

TypeScript, React, NestJS, Prisma, PostgreSQL
Jest, React Testing Library, Playwright
Figma
Terraform, GCP

Bonus qualifications

Fintech experience (payments, compliance, or regulated environments).
Experience with internal developer platforms or developer-experience tooling.
Familiarity with Terraform and GCP, plus observability tooling (logging, metrics, tracing).
Security interest, including OWASP-style practices, secrets management, or dependency/vulnerability scanning.
Exposure to TypeScript/Node.js, NestJS, Prisma, PostgreSQL, and Playwright / React Testing Library.

Sydecar values

Be Committed
Be Excellent
Be Humble
Win Together

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2d ago

Principal Machine Learning Engineer

Okta San Francisco, CA

San Francisco, CA

2d ago

$238k - $326k/yr Full time Backend Developer Agentic Ai Ai Agent

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Job Description

Okta is building agent access authorization capabilities through Okta Secures AI, shifting from static, rule-based checks to dynamic AI security mechanisms. In this Principal Machine Learning Engineer role, you will help define a unified control plane and Identity Security Fabric for the agentic era, enabling real-time threat inspection and behavioral analysis.

Based in San Francisco, CA on a hybrid schedule, you will work on systems that enforce intent, interpret LLM signals, and integrate low-latency ML evaluation into the request path. This position is backed by a USD 238,000 - 326,000 per year salary range and is intended for experienced engineers.

What you will do

Implement intent-based enforcement so agent runtime requests are verified against their intended purpose, supported by required key capabilities.
Apply LLM reasoning and prompt parsing to interpret prompts, tool payloads, and intent in real time.
Integrate low-latency inference or semantic evaluation engines directly into the API gateway request path.
Use embeddings, vector search, or zero-shot classification to score alignment between agent intent and executed actions.
Design confidence-scored decision engines that feed semantic verification results into policy frameworks such as Cedar.
Establish evaluation benchmarks, prompt injection defenses, and guardrails to reduce bypasses and false positives.
Architect scalable ML and Generative AI systems that integrate retrieval, inference, and evaluation pipelines.
Optimize prompting, context retrieval, and RAG workflows for accuracy, safety, and efficiency in Claude-based systems.
Build automated evaluation pipelines to measure model quality, correctness, groundedness, and safety in production.
Implement schema validation, structured output enforcement, and guardrails to support reliable and compliant AI outputs.
Mentor and coach engineers to support team and community growth.

What you bring

10+ years of software development experience with strong programming expertise in Python (familiarity with Go or TypeScript is a plus).
Hands-on experience with applied machine learning, including feature engineering through training and fine-tuning.
Hands-on experience with modern Generative AI platforms including AWS Bedrock, OpenAI, Anthropic, or similar.
Deep understanding of retrieval-augmented generation (RAG), embeddings, and knowledge-base workflows.
Hands-on experience with AI agent frameworks such as LiteLLM, LangGraph, LangChain, LlamaIndex, MCP, or related options.
Familiarity with ML frameworks (FastAPI, PyTorch, TensorFlow, Spark ML) and workflow orchestration tools (for example, Airflow).
Experience defining evaluation metrics, pipelines, and feedback loops for ML and GenAI systems.
Proven ability to collaborate with product and engineering teams to drive greenfield initiatives, navigate unknowns, and iterate frequently and quickly.
Experience building tools or infrastructure for AI/ML applications, with a strong understanding of the developer lifecycle in an AI-native world.

Technologies

Python, Go, TypeScript, AWS Bedrock, OpenAI, Anthropic
LiteLLM, LangGraph, LangChain, LlamaIndex, MCP
FastAPI, PyTorch, TensorFlow, Spark ML, Airflow, Cedar, Claude-based systems

Education

Bachelor’s or Master’s degree in Computer Science or related field.

Benefits

Equity (where applicable), bonus, and benefits including health, dental and vision insurance
401(k)
Flexible spending account
Paid leave including PTO and parental leave

Extra credit

Experience integrating AI-driven systems with identity, authentication, or security products.
Exposure to ethical AI, model risk, or compliance frameworks.
Familiarity with evaluation datasets, synthetic data generation, or LLM-as-a-judge methods.