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data scientist operations

Kikoff

<div>
 
 Kikoff: The Fintech Powering Financial Security at Scale
 
 
 
 Kikoff is a profitable, pre-IPO fintech company on a mission to empower everyone to achieve financial security. With record revenue growth in 2025 and a unicorn valuation, we've built a suite of products that help millions of people build credit, access liquidity, and save money.
 
 
 We're scaling fast. Join us if you want to build something meaningful and help millions of people move forward financially.
 
 
 
 Why Kikoff
 
 
 
 This is a consumer fintech startup, and you will be working with serial entrepreneurs who have built strong consumer brands and innovative products. We value extreme ownership, clear communication, a strong sense of craftsmanship, and the desire to create lasting work and work relationships. Yes, you can build an exciting business AND have real-life real-customer impact.
 
 
 
 About The Role
 
 
 
 As a Operations Data Scientist at Kikoff, you work closely with cross functional teams including Customer Operations, Product Operations, Product, Engineering, and Data Engineering to make our operations smarter, faster, and more customer-centric. Operations sits at the front line of our customer experience, and you will turn the massive amount of unstructured and structured data generated there into decisions, workflows, and tools that improve both agent and customer outcomes.
 
 
 This is a high-ownership role. We are looking for someone with an owner mindset who proactively seeks out opportunities to apply a sharper technical and analytical lens to how Ops runs. You will define your own roadmap as often as you execute against someone else's.
 
 
 
 Your Responsibilities Include
 
 
 
 <ul>
 <li>
 Ops AI ownership: Own and evolve Ops AI, our AI agent that helps Ops investigate customer issues and pull accurate data. Design and iterate on the agent's harness (SQL library, memory, context, skills, tools, guardrails), continuously improve its accuracy and expand its use cases as new workflows emerge.
 </li>
 <li>
 Ops Analytics and Measurement: Use data to shape how Ops runs. Define core Ops metrics, build self-serve dashboards and turn unstructured customer data into insights, design and run experiments to turn ops insights into product changes
 </li>
 <li>
 Cross-Functional Collaboration: Partner with Product Ops, CX Ops, and Operation Agents to translate data into decisions, workflows, and tooling that improve customer and agent outcomes.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelors&rsquo; or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
 </li>
 <li>
 Expert knowledge of SQL
 </li>
 <li>
 Enthusiasm and comfort using AI tools (eg. LLMs, Claude Code) in analytics
 </li>
 <li>
 Strong verbal and written communication skills
 </li>
 <li>
 A humble collaborative can-do attitude, bias to action, and a hunger to apply a technical lens to messy, ambiguous operational problems
 </li>
 <li>
 Solid understanding of statistical analysis, experimentation design, and common ML techniques
 </li>
 <li>
 1-2 years of data science experience
 
 
 </li>
 </ul>
 Nice to Have
 
 
 <ul>
 <li>
 Enthusiasm and comfort with using AI in analytics or for fintech problems
 </li>
 <li>
 Experience with Machine Learning especially in a production environment
 
 
 </li>
 </ul>
 Base Range
 
 
 $160,000 - $260,000 USD
 
 
 Equal Employment Opportunity Statement
 
 
 Kikoff Inc. is an equal opportunity employer. We are committed to complying with all federal, state, and local laws providing equal employment opportunities and considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
 
 
 Please reference the following for more information.
</div>

Data Scientist Operations

Data Scientist, Analytics (Technical Leadership)

Common Sense Media

<div>Data Scientist<div></div><div><div><div><div>
Organization 
Common Sense Media</div><div> 
Department 
Data</div><div> 
Reports To 
Senior Director, Data &amp; Analytics</div><div> 
Location 
San Francisco, CA</div><div><div> 
Classification 
Salary Range</div><div> 
Full-time, Exempt
$140,00&ndash;$166,250</div></div> 
</div></div></div>
POSITION OVERVIEW
Common Sense Media is seeking a Data Scientist to help build data capabilities that allows the organization to answer the questions that matter most to advancing our mission and driving impact for kids and families. This is a hands-on, full-stack individual contributor role responsible for developing pipelines, models, and analyses that turn data from across the Common Sense Media ecosystem into reliable, decision-ready insights.
The Data Scientist will develop predictive and statistical models that support organization-wide decisions, design and analyze experiments, apply causal inference methods, and lead impact analyses that measure how Common Sense Media's work affects kids, families, and educators, translating findings into clear, actionable recommendations for both technical and non-technical audiences. The Data Scientist's work will span the full range of data science at Common Sense Media, from foundational data engineering and data modeling through analytics, machine learning, experimentation, and impact analysis.
As a senior technical voice on the team, the Data Scientist will help uplevel the organization's capabilities in data science, machine learning, and generative AI, advising on methodology, helping to develop and test AI product features, and raising the technical bar within product and engineering.
KEY RESPONSIBILITIES
Analytics &amp; Modeling<ul><li>
Conduct rigorous exploratory and descriptive analyses that establish the foundational understanding of our audiences, programs, and performance.</li><li>
Develop predictive and statistical models that support organization-wide decisions.</li><li>
Apply modern machine learning techniques to ship models and analyses that drive impact.</li></ul>
Experimentation &amp; Causal Inference<ul><li>
Design and execute A/B tests and randomized controlled trials.</li><li>
Leverage rigorous quasi-experimental designs (e.g., difference-in-differences, regression discontinuity) and advanced causal inference techniques to evaluate the impact of complex product and program decisions where randomized testing is not feasible.</li></ul>
Impact Measurement<ul><li>
Lead rigorous impact analyses and program evaluations that measure how Common Sense Media's work affects kids, families, and educators.</li><li>
Apply causal inference and evaluation methods to measure real-world outcomes.</li></ul>
Insights &amp; Communication<ul><li>
Translate findings into clear, actionable recommendations for both technical and non-technical audiences.</li><li><h1 class="jobSectionHeader">
Partner closely with colleagues across Common Sense Media to put data to work across the organization.</h1></li></ul> 
Analytics Engineering<ul><li>
Own the data models that turn raw data into clean, reliable, analysis-ready data sets used across the organization.</li><li>
Work with internal teams and external partners to establish data collection approaches, integrate new data sources, and ensure that incoming data is structured and trustworthy.</li><li><h1 class="jobSectionHeader">
Build and maintain the data pipelines and transformations necessary to support modeling, reporting, and impact measurement.</h1></li></ul> 
Technical Leadership<ul><li>
Serve as a senior technical voice on the team, advising on methodology and raising the technical bar around how to use data in thoughtful decision-making.</li><li>
Help uplevel the organization's capabilities in data science, machine learning, and generative AI, supporting the development and testing of AI tools and features across the organization.</li></ul>
QUALIFICATIONS<ul><li>
8+ years of experience in applied data science, analytics, or a closely related quantitative field, with a track record of shipping models and analyses that have changed decisions.</li><li>
Strong hands-on skills in SQL and Python or R, and expert use of standard machine learning libraries.</li><li>
Experience building and maintaining production data pipelines using modern cloud data warehouses (Snowflake, BigQuery, or Redshift) and modern data stack tooling (dbt, Airflow, Fivetran, or equivalents).</li><li>
Demonstrated experience designing and analyzing experiments, including A/B tests, quasi-experiments, and causal inference methods.</li><li>
Experience leading rigorous impact or program evaluation that measures real-world outcomes.</li><li>
Experience mentoring junior data scientists.</li><li>
Excellent written and verbal communication skills, with the ability to translate technical work into clear narratives for both technical and non-technical audiences.</li><li>
Demonstrated ability to serve as a senior technical voice within an organization, raising the technical bar of teammates and helping non-technical colleagues use data and AI tools effectively in their work.</li><li><h1 class="jobSectionHeader">
Strong understanding of data governance, privacy, and responsible data and AI practices, with particular sensitivity to data involving children and families.</h1></li><li><h1 class="jobSectionHeader">
Familiarity with product analytics, CRM, and marketing platforms (Amplitude, Google Analytics, Salesforce, Braze) and their underlying data structures is a plus.</h1></li><li><h1 class="jobSectionHeader">
Experience building predictive models for subscription, retention, lifetime value, or similar member or customer lifecycle problems is a plus.</h1></li><li><h1 class="jobSectionHeader">
Experience implementing and evaluating generative AI or LLM-based solutions, including prompt engineering, fine-tuning, retrieval-augmented generation, or self-hosted models, with rigorous evaluation against human or ground-truth baselines, is a plus.</h1></li><li><h1 class="jobSectionHeader">
Experience designing AI evaluation frameworks, including human-in-the-loop evaluation, bias and fairness assessment, and ongoing monitoring of model performance, is a plus.</h1></li><li><h1 class="jobSectionHeader">
Prior experience in a mission-driven, nonprofit, education, or media organization is a plus.</h1></li></ul>
WHAT WE OFFER<ul><li>
The opportunity to really make a difference in the lives of kids and families!</li><li>
A mission-driven team with a 23-year track record of impact for families and children.</li><li>
Competitive nonprofit compensation and comprehensive benefits.</li><li>
A collaborative, flexible work environment with meaningful leadership access and visibility.</li></ul>
ABOUT COMMON SENSE MEDIA
Common Sense Media is the leading nonprofit organization dedicated to improving the lives of kids and families by providing the research-backed information, education, and independent voice they need to thrive in the age of apps, algorithms, and AI. We rate, educate, and advocate for policies to protect and prepare kids online. Our ratings, research, and resources reach more than 150 million users globally, over 1.4 million educators, and more than 100,000 schools worldwide every year. Learn more at commonsense.org.</div>

Data Scientist

Prolific

<div>
 
 AI Trainer &ndash; Research Scientists
 
 
 
 
 
 About Prolific
 
 
 
 
 Prolific is not just another player in the AI space &ndash; we are building the biggest pool of quality human data in the world.
 
 
 Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.
 
 
 
 
 The role
 
 
 
 
 We&rsquo;re looking for people with Research Scientist experience to work as self-employed AI Trainers to help train and evaluate cutting-edge AI models from some of the world&rsquo;s biggest AI labs. If you have the necessary experience, we&rsquo;ll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you&rsquo;ll be invited to join Prolific as a Domain Expert participant, where you&rsquo;ll get paid to train and evaluate powerful AI models.
 
 
 Researchers looking for your skills tend to pay up to $50/hr subject to the length of tasks available. If successful, you must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter.
 
 
 
 
 What you&rsquo;ll be doing in the role
 
 
 
 
 Completing AI training tasks such as analyzing, editing, and writing research-focused content
 
 
 Judging the performance of AI on research design, methodology, and scientific reasoning prompts
 
 
 Improving cutting-edge AI models using your experience in research and experimentation
 
 
 
 
 What you&rsquo;ll bring
 
 
 
 
 Experience working as a Research Scientist or in a closely related research role
 
 
 A strong understanding of scientific methodology, experimental design, and data analysis
 
 
 A willingness to take our skills verification test to assess your suitability for our Domain Expert participant pool
 
 
 Strong attention to detail and the ability to concentrate on complex tasks for up to one hour at a time
 
 
 A reliable and fast internet connection and access to a computer
 
 
 A Paypal account to receive payment from our clients*
 
 
 
 
 Why Prolific is a great platform to join as a Domain Expert participant
 
 
 
 
 Joining our platform as a Prolific participant will give you the chance to influence the AI models of the future. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.
 
 
 We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.
 
 
 We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation &ndash; one that reflects the breadth and the best of humanity.
 
 
 <ul>
 <li>
 Participants are self-employed and need to declare earnings to their respective tax authorities. Prolific has no liability for any tax obligations or reporting requirements resulting from compensation received through this platform. Each participant is solely responsible for compliance with applicable tax laws in their jurisdiction.
 
 
 </li>
 </ul>
 
 Links to more information on Prolific
 
 
 
 Website
 
 
 Youtube
 
 
 Privacy Statement
 
 
 By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal information.
</div>

AI Training - Research Scientist (PST)

<div>
 As a Data Scientist at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Oculus). By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
 
 
 Data Scientist, Product Analytics Responsibilities:
 
 
 <ul>
 <li>
 Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
 </li>
 <li>
 Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
 </li>
 <li>
 Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
 </li>
 <li>
 Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations
 </li>
 <li>
 Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
 
 
 </li>
 </ul>
 Minimum Qualifications:
 
 
 <ul>
 <li>
 A minimum of 6 years of work experience in analytics (minimum of 4 years with a Ph.D.)
 </li>
 <li>
 Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R)
 
 
 </li>
 </ul>
 Preferred Qualifications:
 
 
 <ul>
 <li>
 Master's or Ph.D. Degree in a quantitative field
 </li>
 <li>
 Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
 </li>
 <li>
 Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
 </li>
 <li>
 Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
 
 
 </li>
 </ul>
 About Meta:
 
 
 Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today&mdash;beyond the constraints of screens, the limits of distance, and even the rules of physics.
 
 
 Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
 
 
 Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
 
 
 $177,000/year to $247,000/year + bonus + equity + benefits
 
 
 Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
</div>

Data Scientist, Product Analytics

Workato

<div><div><h1 class="jobSectionHeader">About Workato</h1>

Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato&rsquo;s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com
<h1 class="jobSectionHeader">
Why join us?</h1>

Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.

But, we also believe in balancing productivity with self-care. That&rsquo;s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.

If this sounds right up your alley, please submit an application. We look forward to getting to know you!

Also, feel free to check out why:
<ul>
<li>Business Insider named us an &ldquo;enterprise startup to bet your career on&rdquo;
</li>
<li>Forbes&rsquo; Cloud 100 recognized us as one of the top 100 private cloud companies in the world
</li>
<li>Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
</li>
<li>Quartz ranked us the #1 best company for remote workers
</li>
</ul></div><div><h2 class="jobSectionHeader">Senior AI Engineer &ndash; Developer Products</h2>

Location: San Francisco, CA (Onsite/Hybrid)
<h3 class="jobSectionHeader">
About the Role</h3>

We are seeking an exceptional Senior Software Engineer to join our San Francisco team and build new developer products. In this role, you will design, build, and optimize AI-first experiences that empower developers to experiment, prototype, and integrate with our platform. You will collaborate closely with product, engineering, and developer relations teams to deliver robust, scalable, and intuitive services. This role requires a high technical bar, plus an emphasis on developer ergonomics, so we can deliver a delightful developer experience.
<h3 class="jobSectionHeader">
Responsibilities</h3>
<ul><li>Design, build, and enhance AI services and APIs powering our developer sandbox, leveraging LLMs and custom ML models.</li>
<li>Develop well-architected, testable, and efficient Python code to support rapid prototyping and experimentation.</li>
<li>Implement and improve validation, monitoring, and observability for ML services within the sandbox environment.</li>
<li>Drive the full development lifecycle: from ideation and architecture to deployment and continuous improvement.</li>
<li>Collaborate with cross-functional teams to design developer-centric solutions and intuitive user experiences.</li>
<li>Continuously evaluate and optimize existing implementations for performance, scalability, and developer usability.</li>
<li>Identify and resolve bottlenecks, bugs, and technical challenges in a fast-paced, iterative environment.</li>
<li>Conduct code reviews and mentor team members to uphold high engineering standards.</li>
</ul><h3 class="jobSectionHeader">Requirements</h3>
<h4 class="jobSectionHeader">Qualifications / Experience / Technical Skills</h4>
<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, Information Systems, or equivalent industry experience.</li>
<li>5+ years of experience as an ML Engineer, Data Scientist, or similar role.</li>
<li>Strong Python programming skills and hands-on experience with NLP and LLM models.</li>
<li>Proven track record of deploying and maintaining ML services in production environments.</li>
<li>Solid understanding of network protocols, API design, and developer tooling.</li>
<li>Experience with relational and non-relational databases.</li>
<li>LLMops/MLops experience is a strong plus, especially in developer-facing products.</li>
<li>Experience building or supporting developer platforms, APIs, or sandbox environments is highly desirable.</li>
</ul><h4 class="jobSectionHeader">Soft Skills / Personal Characteristics</h4>
<ul><li>Collaborative team player with a passion for empowering developers and improving developer experience.</li>
<li>Adaptable, proactive, and creative&mdash;comfortable working in a dynamic, startup-like environment.</li>
<li>Strong problem-solving skills and a continuous improvement mindset.</li>
</ul>
Join us in San Francisco and help shape the future of developer innovation with AI-powered sandbox experiences! 
 
The salary range for this role is dependent on experience and ranges from $170,000 to $250,000. We also provide stock options to all employees and generous benefits.</div></div>

Senior AI Engineer – Developer Products

Tamarind Bio

<div><h1 class="jobSectionHeader">About Tamarind Bio</h1>
We enable any scientist to access AI-powered drug discovery. Thousands of scientists from large pharma companies, top biotechs, and academic institutions use Tamarind to design protein drugs, improve industrial enzymes, and create cutting edge molecules that weren&rsquo;t feasible until now.
New AI models are quickly eclipsing physics-based tools in computational drug discovery. Scientists often struggle to fine-tune, deploy, and scale these models, leaving breakthroughs on the table. Tamarind provides a simple interface to the vast array of tools being released daily.
Staff Software Engineer / Technical Lead
We're hiring a Staff Software Engineer to provide technical leadership across our engineering team as we continue to scale the platform behind Tamarind.
Today, our engineering team consists primarily of early and mid-career engineers. As the complexity of our systems and customer requirements continues to grow, we're looking for someone who can help guide technical decision-making, mentor engineers, and drive architectural discussions across the organization.
This is not an engineering management role.
We're looking for a hands-on technical leader who enjoys writing code, reviewing designs, solving difficult engineering problems, and helping other engineers grow. You'll work closely with the CTO to shape technical direction while remaining deeply involved in execution.
The role spans architecture, infrastructure, product development, code reviews, technical mentorship, and engineering best practices.
What You'll Do<ul><li>
Partner with the CTO on architecture, technical planning, and major engineering initiatives</li><li>
Provide technical guidance across a team of 7-8 engineers</li><li>
Lead design reviews and architectural discussions</li><li>
Help engineers navigate complex technical challenges</li><li>
Contribute directly to the codebase across infrastructure, backend services, APIs, and product development</li><li>
Review code and provide feedback on implementation approaches</li><li>
Identify opportunities to improve reliability, scalability, performance, and developer productivity</li><li>
Support technical decision-making across new products and platform capabilities</li><li>
Work closely with customers and internal stakeholders to understand requirements and translate them into practical solutions</li><li>
Help establish engineering standards as the team continues to grow</li></ul>
Week in the Life<ul><li>
Collaborate with the CTO on technical priorities and architectural decisions</li><li>
Review designs and provide guidance on implementation approaches</li><li>
Build and operate services across infrastructure, ML systems, APIs, and customer-facing applications</li><li>
Participate in code reviews and technical discussions</li><li>
Help unblock engineers working through difficult technical problems</li><li>
Work directly with customers to understand requirements and gather feedback</li><li>
Balance hands-on engineering work with technical leadership responsibilities</li></ul>
Ideal Qualifications<ul><li>
7+ years of software engineering experience</li><li>
Experience serving as a senior technical contributor, staff engineer, principal engineer, or technical lead</li><li>
Strong software architecture and distributed systems experience</li><li>
Experience building and operating production infrastructure and cloud services</li><li>
AWS experience (EC2, S3, DynamoDB, Docker, etc.)</li><li>
Ability to mentor engineers and provide technical guidance across multiple projects</li><li>
Strong communication skills and sound engineering judgment</li><li>
Comfort operating in an early-stage startup environment</li><li>
Willingness to work onsite in San Francisco</li></ul>
Technology
Our technology sits at the intersection of DevOps, MLOps, and Computational Biology. We support workloads ranging from large-scale ML inference and model deployment to workflow orchestration across research, infrastructure, and scientific computing environments.
The role requires someone who enjoys moving between architecture, implementation, operations, and mentorship while helping a growing engineering team tackle increasingly complex technical challenges.
Compensation Range: $150K - $250K</div>

Staff Software Engineer / Technical Lead

Explore 117+ Data scientist operations in San Francisco this July. Find roles across top companies and apply now to boost your career.