data engineer

data scientist

advisor - scientific data engineer Jobs in San Francisco

advisor - scientific data engineer

ai engineer, ai & data platforms (aidp) Jobs in San Francisco

ai engineer, ai & data platforms (aidp)

ai engineering lead Jobs in San Francisco

ai engineering lead

machine learning engineer

Verse

<div>
 
 Location:
 
 San Francisco, CA (Hybrid)
 
 
 
 What is Verse?
 
 
 
 Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world&rsquo;s largest energy buyers, managing energy has never been more complex or more critical.
 
 
 Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence&mdash;replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs.
 
 
 
 The Role
 
 
 
 Verse is seeking a Data Scientist to join our Data Science Team. In this role, you will lead the development and deployment of advanced data-driven solutions across a range of applications, including electricity markets, renewable procurement, and energy risk management. You will shape the machine learning and data modeling foundations that Verse's software is built on. For example, you might spend a cycle deploying electricity market price forecasting pipelines for new regions, developing solar production anomaly detection models, or creating scalable tools for benchmarking energy project financial performance.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 
 Lead End-to-End Data Science Projects:
 
 Own and drive projects from problem definition through scoping, modeling, validation, and production deployment. Translate business problems into scalable, high-impact modeling solutions.
 </li>
 <li>
 
 Statistical &amp; Machine Learning Modeling:
 
 Design, develop, and refine statistical and machine learning models (e.g., time series forecasting, probabilistic models) to support decision-making and enhance product capabilities.
 </li>
 <li>
 
 Analytics Engineering &amp; Data Modeling:
 
 Perform complex data transformations and develop well-structured data models. Translate business and analytical requirements into scalable, tested, and well-documented datasets.
 </li>
 <li>
 
 Software Development &amp; Productionization:
 
 Write clean, efficient, and maintainable Python code. Contribute to integrating models into production systems in a cloud-based environment while leveraging AI coding tools to accelerate development.
 </li>
 <li>
 
 MLOps:
 
 Contribute to Verse&rsquo;s machine learning modeling infrastructure to support scaling of ML models and improving reliability, monitoring, and performance in production.
 </li>
 <li>
 
 Cross-Functional Collaboration:
 
 Partner with product, engineering, and business stakeholders to ensure models and insights are aligned with user needs and effectively integrated into workflows.
 
 
 </li>
 </ul>
 
 What We're Looking For (Minimum Qualifications)
 
 
 
 <ul>
 <li>
 Master&rsquo;s degree in Computer Science, Statistics, Engineering, Applied Mathematics, or a related quantitative field and 2+ years of professional experience in data science or machine learning; or
 </li>
 <li>
 Bachelor&rsquo;s degree and 4+ years of professional experience in data science or machine learning
 </li>
 <li>
 Strong foundation in statistical modeling and machine learning, including time series forecasting and model evaluation
 </li>
 <li>
 Experience deploying and maintaining models in cloud-based environments (e.g., AWS, GCP, or Azure) using MLOps practices
 </li>
 <li>
 Strong Python expertise, including experience with scientific computing and ML libraries (e.g., NumPy, pandas, scikit-learn, PyTorch, TensorFlow)
 </li>
 <li>
 Hands-on experience in orchestrating complex data transformations (e.g. Airflow, Dagster, dbt)
 </li>
 <li>
 Strong software engineering practices (version control, testing, code reviews, CI/CD)
 </li>
 <li>
 Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders
 
 
 </li>
 </ul>
 
 What Will Make You Standout (Preferred Qualifications)
 
 
 
 <ul>
 <li>
 Experience in energy, climate tech, or related domains (not required)
 </li>
 <li>
 Familiarity with optimization methods or operations research
 </li>
 <li>
 Experience developing probabilistic forecasting models and quantifying uncertainty
 </li>
 <li>
 PhD in a quantitative field
 
 
 </li>
 </ul>
 
 What Makes Verse a Great Place to Work?
 
 
 
 <ul>
 <li>
 
 Lead with Empathy:
 
 We lift each other up with humility and kindness, always putting colleagues and customers first
 </li>
 <li>
 
 Be Honest &amp; Transparent:
 
 We prioritize effective communication to build trust with our team, customers, and stakeholders
 </li>
 <li>
 
 Move with Balance &amp; Precision:
 
 We believe speed and perseverance must be accompanied by thoughtfulness and reflection
 </li>
 <li>
 
 Leave the World a Better Place:
 
 We are passionate about our mission, and we strive to create a sustainable world for future generations
 
 
 </li>
 </ul>
 
 Base Pay Range
 
 
 
 $146,000 - $172,000
 
 
 
 This is the estimated base salary range for this position, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs.
 
 
 
 
 Benefits and Employee Perks
 
 
 
 <ul>
 <li>
 Competitive compensation and equity grant at a high-growth start up
 </li>
 <li>
 Comprehensive benefits package including medical, dental and vision insurance, and 401k
 </li>
 <li>
 Flexible hours and unlimited PTO
 </li>
 <li>
 Diverse and inclusive working environment
 
 
 </li>
 </ul>
 Verse is an equal opportunity employer. All applicants and employees are considered for hire, promotion, and compensation without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, marital or familial status.
</div>

Data Scientist

Apple

Do you have a passion for invention and self-challenge? Do you thrive on pushing the limits of what&rsquo;s considered feasible? As part of a world class modem team, you&rsquo;ll craft sophisticated leading-edge embedded firmware that deliver more performance in our products than ever before. You&rsquo;ll work across disciplines to transform improved hardware elements into a single, integrated design. 
 
Join us, and you&rsquo;ll help us innovate new wireless systems technologies that continually outperform the previous iterations. By collaborating with other product development groups across Apple, you&rsquo;ll push the industry boundaries of what wireless systems can do and improve the product experience for our customers across the world. Do you want to have an impact on every single Apple product? As a Cellular Data &amp; Automation Engineer, you will be at the center of the embedded 5G/4G/multimode cellular firmware effort within a silicon design group responsible for designing and productizing state-of-the-art cellular SoCs. 
 
Description 
 
As a Data &amp; Automation Engineer, you will be responsible for developing new features to enhance test automation system for improving test efficiency and stability. Furthermore, you will be participating in developing state-of-the-art data processing pipeline and leveraging data science algorithms &amp; machine learning models to parse massive data and logs in timely manner to automatically solve the issues or provide recommendations for the next step. In addition, you will be closely partnering with FW engineering teams in integrating and deploying models and data processing pipeline as part of entire automation system to deliver analysis results to benefit FW engineers in debugging issues. You will work with amazing team, brainstorm new ideas, and develop models and algorithms to solve complicated problems that have a substantial impact.&quot;,&quot;responsibilities&quot;:&quot;Develop new features to enhance the automation system based on the business&rsquo;s needs 
 
Develop and maintain real-time data processing pipelines to ensure processing accuracy and efficiency 
 
Collaborate closely with AI/ML engineers to integrate new AI pipelines and ML models into the production system and ensure achieving expected results and efficiency 
 
Integrate various internal tools and external tools into the existing automation system and/or data processing pipelines to enable new applications 
 
Provide technical support for users and help troubleshoot issues to unblock projects 
 
Preferred Qualifications 
 
Master&rsquo;s degree in data science or computer science or machine learning is preferred. 
 
Proficient in scripting or programming languages such as Python, Java, C/C++ with 5+ years of proven programming skills. 
 
Advanced SQL skills with the ability to write complex joins and nested queries. 
 
Proficiency in data visualization tools (such as Tableau, D3) and strong understanding of data manipulation and querying using SQL and Python together. 
 
Experience with dashboards and interactive reports. Ability to work with large datasets and conduct data cleaning and transformation. 
 
Experience with automation tools and frameworks, e.g. Jenkins, Gitlab CI/CD. 
 
Ability to leverage data science algorithms and machine-learning models to solve various kinds of issues. 
 
Experience in utilizing analytics and statistical methods to transform data into useful insights and actionable results. 
 
Ability to think creatively and identify, build, and support solutions and roadmaps focused on automation and reduction of manual processes. 
 
Strong critical thinking and communication skills with the ability and desire to learn and evaluate new technologies. 
 
Minimum Qualifications 
 
BS and a minimum of 3 years relevant industry experience. 
 
Proficient developer with 3+ years proven programming skills using Python, Pandas, Matplotlib and other key related tools. 
 
Solid knowledge and experience with relational database (e.g Postgres) and non-relational database (e.g.Mango DB). Ability to write complex queries with SQL is required. 
 
Experience with dashboards and interactive reports. Proficiency in data visualization tools (such as Tableau) and a strong understanding of data manipulation and querying using SQL and Python together. 
 
Ability to think creatively and identify, build, and support solutions and roadmaps focused on automation and reduction of manual processes. 
 
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 . 
 
Pay &amp; Benefits 
 
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 $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
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. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Cellular Data & Automation Engineer

Octave

<div><h3 class="jobSectionHeader">About the Company:</h3>

Octave is a modern behavioral health practice creating a new standard for care delivery that's both high-quality and accessible. With in-person and virtual clinics in multiple states, the company offers evidence-based individual, couples, and family therapy, while pioneering relationships with payers to make care more affordable through insurance. By raising the bar on how care is delivered and how providers are supported, we are building a sustainable system that values equity, affordability, and effectiveness.
<h3 class="jobSectionHeader">
Job Summary:</h3>

We're looking for a Sr. Data Engineer with strong data platform experience to help evolve our modern data stack and contribute to the foundation of our emerging AI and ML platform. This role sits at the intersection of data engineering, platform architecture and machine learning enablement and will bring high-quality, scalable, and ethical AI into real-world use. You will partner closely with data scientists, analysts, and product managers to ensure our platform supports reliable data pipelines, scalable analytics, and production ready machine learning systems in addition to defining new architecture, best practices, and patterns for fellow engineers to inherit. The ideal candidate is both a systems thinker and a hands-on builder who thrives in evolving environments and is passionate about creating reliable data infrastructure that enables peers and partner teams to move faster with data.
<h3 class="jobSectionHeader">
Duties &amp; Responsibilities:</h3>
<ul><li>Design, build, and maintain scalable systems for ingestion, transformation, and storage of data, with a focus on testing and observability.</li>
<li>Implement frameworks, tooling, and automation to safely increase development velocity.</li>
<li>Develop foundational end-to-end AI/ML workflows from (1) source ingestion and preparation, (2) training and tuning, (3) experimentation and productionization, and (4) downstream systems integration (EHR modules, micro-services, dashboards).</li>
<li>Support iterative model development and production operations and observability (accuracy, drift, bias, fairness, reproducibility).</li>
<li>Contribute to a culture of continuous improvement, knowledge-sharing and mentoring of peer engineers.</li>
<li>Leverage AI tools as a core part of daily work (drafting, research, iteration) to improve efficiency, quality, and decision-making.</li>
</ul><h3 class="jobSectionHeader">Required Skills:</h3>
<ul><li>Proficiency in SQL and Python with strong familiarity towards modern data engineering frameworks, infrastructure, and tooling.</li>
<li>Proficiency with data ops best practices, monitoring, pipeline automation, and CI/CD.</li>
<li>Knowledge of modern compute and ML frameworks/libraries (i.e., Spark, TensorFlow, PyTorch, scikit-learn).</li>
<li>Ability to build production APIs and services, inclusive of MCP servers that expose internal data/services to LLMs.</li>
<li>A collaborative mindset, dependable execution, drive to reflect and improve, and humility to ask questions and learn.</li>
<li>Comfort using AI tools in day-to-day workflows, with a willingness to continuously rethink and improve how work gets done.</li>
<li>Curiosity and openness to experimenting with new tools and approaches; prior experience with AI tools is a plus.</li>
</ul><h3 class="jobSectionHeader">Education &amp; Experience:</h3>
<ul><li>Bachelor's degree (or equivalent) in Computer Science, Data Science, Statistics, Engineering or a related field.</li>
<li>5+ years of experience in data engineering, platform engineering, or ML engineering.</li>
<li>Experience working with major cloud data platforms and tools:</li>
<li>Preferred experience:</li>
<li><ul><li>Healthcare, behavioral health, EHR systems, and/or regulated industries.</li>
<li>Specific expertise with: AWS/GCP, dbt, AirflowAirbyte, Redshift/BigQuery.</li>
</ul></li></ul><h3 class="jobSectionHeader">Octave's Company Values:</h3>

The below values drive our day-to-day operations.
<ul>
<li>We're human beings first. We operate with empathy and kindness &ndash; with our clients, with our collaborators, and with ourselves.</li>
<li>People deserve better than status quo. We're willing to tackle the intractable problems, no matter how big, because someone should. We ask big questions, we craft big solutions, and we challenge ourselves and others to make it happen.</li>
<li>No bystanders. No stars. No tourists. Each person has been selected to be here, and with that comes a responsibility to bring your expertise, share your ideas, and help make this company better.</li>
<li>Partnership paves the path ahead. We don't operate in a silo, internally or externally. To transform the system, we believe in working with others to create something bigger, better, and stronger.</li>
<li>Quality is crucial at scale. Quality is core to our business, and we refuse to sacrifice it as we grow.</li>
<li>Progress is a process. In the pursuit of progress, we iterate, reflect, learn, adjust &ndash; and always leave things better than we found them.</li>
<li>There are people behind every data point. We recognize that numbers tell only one part of the story, and we also do the work to understand impacts at the individual level.</li>
</ul><h3 class="jobSectionHeader">Physical Requirements:</h3>
<ul><li>Prolonged periods sitting at a desk and working on a computer.</li>
<li>Must be able to frequently communicate with others through virtual meeting applications such as Zoom and Google Meet.</li>
<li>Must be able to observe and communicate information on company provided laptop.</li>
<li>Move up to 10 pounds on occasion.</li>
<li>Must be eligible to work in the United States without sponsorship now or in the future.</li>
</ul><h3 class="jobSectionHeader">Compensation, Equity &amp; Incentives:</h3>

Base Salary Range Octave is committed to pay equity and transparency. Our salary ranges are determined by role, level, and location/ zone. Final pay within the posted range will be decided based on a combination of job-related factors, including education, training, experience, and market demands.
<ul>
<li>Geo 1 (All other states &amp; D.C.): $142,600 - $153,100</li>
<li>Geo 2 (CO, HI, MD, RI): $156,900 - $168,400</li>
<li>Geo 3 (AK, CA, CT, MA, NJ, NY, WA): $164,000 - $176,000</li>
</ul>
Variable Compensation &amp; Equity
<ul>
<li>Performance Bonus: This role is not currently eligible for bonus incentives.</li>
<li>Equity Awards: This role is eligible to participate in Octave's equity program via Stock Options, subject to the terms of the applicable Equity Incentive Plan.</li>
<li>Remote Work Stipend: New full-time employees receive a $300 equipment reimbursement to support a home office setup.</li>
<li>Internet &amp; Phone Reimbursement: Full-time employees are eligible for a monthly reimbursement of up to $75 for internet and cell phone related expenses.</li>
</ul>
Octave is committed to pay equity and transparency. Octave will not discharge or in any other manner coerce, intimidate, threaten, discriminate or retaliate against employees or applicants because they have: (i) inquired about, discussed, compared, or disclosed their own wages, benefits, or other compensation, or the wages, benefits, or other compensation of another employee or applicant; (ii) asked Octave to provide a reason for the employee's wages or lack of opportunity for advancement; or (iii) aided or encouraged others in exercising their rights to discuss wages, compensation, or benefits, or to seek pay equity.

However, except as otherwise provided by law, employees who have access to the compensation information of other employees or applicants as part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) in compliance with the company's legal duty to furnish information under applicable law .
<h3 class="jobSectionHeader">
Comprehensive Benefits:</h3>

At Octave, we believe in supporting the &quot;human being first&quot;. Here's a snapshot of the benefits available to eligible employees:
<ul>
<li>Health &amp; Wellness: Choose what works best for you with one High Deductible Health Plan (HDHP) and two PPO medical plan options, plus comprehensive Dental and Vision coverage.</li>
<li>Medical Support: Enjoy access to a company-sponsored membership with One Medical for convenient, modern care.</li>
<li>Retirement: Plan for your future with a 401(k) that offers both traditional and Roth options.</li>
<li>Paid Time Off: Time to recharge matters. Take advantage of a generous time off policy, up to 15 paid company holidays, and accrued sick time.</li>
<li>Financial Protection: We've got you covered with company-paid Life, AD&amp;D, and Disability insurance, plus optional extras like Pet, Legal, and Worksite plans (Critical Illness, Hospital Indemnity, and Accident).</li>
<li>Parental Leave (Bonding Time): Growing your family? Full-time employees can take paid bonding leave after 6 months, whether it's a new baby, adoption, or foster placement. Time off increases with tenure.</li>
<li>Growth: Keep learning and leveling up with professional development reimbursement for role-related growth opportunities.</li>
</ul><h3 class="jobSectionHeader">How We Use Technology in Hiring:</h3>

As part of our hiring process, we may use technology tools, including AI-supported systems, to assist with reviewing applications or documenting interviews. These tools are designed to support our team, not replace human judgment, and final hiring decisions are always made by our team.

This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice.<div>
Application Instructions:

Please complete the following application. Please note that the U.S. Equal Opportunity Employment Information questions below are used for the purposes of EEOC reporting and are optional to complete. Octave is unable to change these questions and we acknowledge that many of the U.S. Equal Opportunity Employment Information questions are not inclusive or affirming of all aspects of cultural identity. Octave is committed to an inclusive workplace environment, and this information will not inform how we approach hiring or employment.</div></div>

Sr. Data Engineer

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we&rsquo;re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain &mdash; and we&rsquo;re looking for talented people who want to help. 
 
You&rsquo;ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You&rsquo;ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you&rsquo;ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
 
 
The Data Center Field Engineering Team is the engineering owner for the lifecycle of AWS data center mechanical and electrical infrastructure. This includes supporting new designs and innovations through data center end-of-life, with a focus on root cause analysis of failures, capacity and availability improvement, and optimization of the existing fleet. 
 
As a Senior Data Scientist on the Field Engineering Portfolio team, you will bring advanced analytical and machine learning capabilities to one of the most critical infrastructure organizations at AWS. You will develop scalable models and data-driven frameworks that measure, predict, and improve fleet performance &mdash; including data center availability, operational efficiency, and key performance indicators (KPIs) across the global AWS data center fleet. 
 
You are an exceptionally strong communicator, both written and verbally, capable of translating complex quantitative findings into clear recommendations for senior engineering and business leadership. You will work cross-functionally with Field Engineers, Operations, Commissioning, and Construction teams to ensure that data science solutions are grounded in operational reality and drive measurable impact. 
 
You will partner with engineering teams and program managers to define metrics, identify performance gaps, and build the analytical infrastructure needed to support strategic decisions at hyper-scale. You must be adept at operating in ambiguous, fast-moving environments where speed of insight can matter as much as analytical precision. 
 
The ideal candidate brings strong problem-solving skills, stakeholder communication skills, and the ability to balance technical rigor with delivery speed and customer impact. You will develop scalable analytical approaches to evaluate performance across the data center fleet to identify regional and site-specific insights, design and run experiments, and shape our development roadmap. You will build cross-functional support within the Data Center Community to assess business problems, define metrics, and support iterative scientific solutions that balance short-term delivery with long-term science roadmaps. 
 
Key job responsibilities 
<ul><li>Develop and maintain scalable models and analytical frameworks to measure and predict data center fleet performance, including availability, efficiency, and reliability KPIs across the global AWS infrastructure portfolio.</li><li>Apply advanced statistical and machine learning techniques to extract actionable insights from complex, large-scale operational datasets generated by data center systems (power, cooling, controls, etc.).</li><li>Partner with Field Engineers, Operations, and Portfolio Managers to identify high-impact opportunities for capacity and availability improvement, translating engineering domain knowledge into quantitative problem formulations.</li><li>Design and implement end-to-end data science workflows &mdash; from data acquisition and cleaning through model development, validation, and production deployment &mdash; enabling repeatable, scalable analysis.</li><li>Formalize assumptions about how data center systems are expected to perform and develop methods to systematically identify deviations, root causes, and high-ROI improvement opportunities.</li><li>Build self-service datasets, dashboards, and reporting mechanisms that provide Field Engineering leadership with real-time visibility into fleet health and portfolio performance.</li><li>Prepare narratives and data-driven recommendations for executive leadership that articulate decision points relative to fleet investment, risk trade-offs, and strategic priorities.</li><li>Collaborate with applied science, software engineering, and data engineering teams to ensure models integrate seamlessly with upstream and downstream systems.</li></ul> 
About the team 
Why AWS 
Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 
 
Diverse Experiences 
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn&rsquo;t followed a traditional path, or includes alternative experiences, don&rsquo;t let it stop you from applying. 
 
Work/Life Balance 
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud. 
 
Inclusive Team Culture 
Here at AWS, it&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 
 
Mentorship and Career Growth 
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience</li><li>4+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience</li><li>Master's degree in a quantitative field such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Engineering, or Computer Science; OR Bachelor's degree and 8+ years of professional experience in a quantitative role.</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience</li><li>Experience documenting modeling for technical and business leaders</li><li>Experience working with data engineers and business intelligence engineers collaboratively</li><li>Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)</li><li>Experience developing operational processes and data insights</li><li>Experience with anomaly detection, predictive maintenance, or reliability modeling in industrial or infrastructure contexts.</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, San Francisco - 183,000.00 - 247,600.00 USD annually 
USA, WA, Bellevue - 159,200.00 - 215,300.00 USD annually 
USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually</div>

Sr. Data Scientist, Field Engineering

Hex Technologies

SF or NYC
 About the role
 
Hex is an AI-powered platform for modern Data Science and Data Analytics workflows. AI Research Engineers at Hex partner with product teams to build industry-leading AI experiences such as the Notebook Agent. In the process, AI Research Engineers will run experiments, fine-tune models, deploy AI infrastructure, and build and maintain experimentation tooling.
 
As an AI Research Engineer partnered with Hex's product teams, your focus will be driving Hex's context engine and pushing forward the capabilities of our Notebook Agent. Built for people doing the most complex and impactful data work in an organization, the Notebook Agent is a highly technical data copilot that writes SQL and python, builds beautiful reports and visualizations, and collaborates with the analyst on new avenues of inquiry. Whether its pushing the frontiers of SQL generation quality or using LLMs to evaluate agent threads, your job will be to enable the data teams that work in Hex to build out highly accurate and curated data experiences for their stakeholders, unlocking the power of data driven decisions for the rest of the business.
 
If you’re a strong builder excited to bring these capabilities to thousands of users, come do it on the best Data Science platform around, with the best user context.
 
We are looking for a senior engineer (from an AI Eng, SWE or MLE background) eager to rapidly expand our capabilities in several greenfield applications. As one of our team’s early hires, you will work on a variety of initiatives including:
 
Building features and experiences from 0 to 1
 Partnering on determining the architecture and stack for our AI-enabled capabilities
 Shipping product experiences that fundamentally change the way that Data Scientists and Analysts operate
 Working at the cutting edge of production AI applications
 
This type of ownership will provide incredible opportunities for personal and professional growth. You will have ample technical and team leadership opportunities, depending on your interests.
 
We aim to deliver AI capabilities that radically accelerate and augment the data science workflow – we’ve got an exciting roadmap and are willing to share more details during the process. We’re particularly interested in candidates who bring inspired excitement about what is possible in this space.
 
We'd love to hear from you if you have: 
Experience getting AI/ML capabilities into production and serving real users – we’re not currently looking for new grad folks.
 A lot of enthusiasm for applications of AI to real business problems.
 Understanding of core MLOps/SW Architecture concepts for modern ML-based applications.
 Ideal candidates are strong on Infra aspects of MLOps as well.
 You’re comfortable working in both Python & JS/TS – it’s okay if you’re only strong in one, but openness to both is important.
 Experimentalist mindset – understanding that quick iteration, and discerning critical thinking, can yield rapid progress on new challenges.
 Interest in the data space, and a love of shipping great products and building tools that empower end users to do more.
 Experience maintaining a high quality bar for design, correctness, and testing.
 Our stack
 
Our product is a web-based notebook and app authoring platform. Our frontend is built with Typescript and React, using a combination of Apollo GraphQL and Redux for managing application state and data. On the backend, we also use Typescript to power an Express/Apollo GraphQL server that interacts with Postgres, Redis, and Kubernetes to manage our database and Python kernels. Our backend is tightly integrated with our infrastructure and CI/CD, where we use a combination of Terraform, Helm, and AWS to deploy and maintain our stack.
 
This is a full-time role based out of either our San Francisco or New York office. Employees are encouraged to come into the office at least twice a week, with Tuesdays and Thursdays being our main in-person days.
 
In addition to our unique culture, Hex proudly offers a competitive total rewards package, including but not limited to, market-benched salary & equity, comprehensive health benefits, and flexible paid time off.
 
The salary range for this role is: $214,000 - $285,000
 
The salary range shown may be a reflection of additional factors such as geographical location and skill ranges/levels we’re open to. Placement in the salary range will be decided upon completion of the interview process, taking into account factors like leaving room for growth, internal fairness & parity, your demonstrated skills, and the depth of your experience. Our Recruiting team will be able to provide more details during the interview process.
 
By submitting an application the candidate consents to the use of their personal information in accordance with the Hex Privacy policy: https://learn.hex.tech/docs/trust/privacy-policy.
 
About Hex
 
Hex is growing our team of builders on a mission to make everyone a data person. Our platform solves key pain points with today's data and analytics tooling, and empowers anyone to explore data using natural language, with or without code, on trusted context. Thousands of customers like Ramp, Figma, Stubhub, Anthropic, and Gamma love Hex for our beautiful UI, agentic superpowers, and boundless flexibility.
 
Hex has raised over $100M from leading investors like Sequoia, a16z, Snowflake and Amplify. With office hubs in San Francisco and New York, as well as remote team members throughout the US and UK, we're a high-agency team that ships fast and has fun doing it. Check out our Intro to Hex video and employee handbook to learn more about what it's like to work at Hex.

AI Research Engineer

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. 
 
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! 
 
Description 
 
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. 
 
Build prototypes to evaluate architecture and modeling approaches, working closely with engineering teams to transition concepts into robust systems. 
 
Guide architectural decisions across LLM applications, multimodal systems, and agentic frameworks. 
 
Assess and integrate open-source tools, orchestration frameworks, context management solutions, and vector databases. 
 
Collaborate with product and business teams to define KPIs and ensure alignment of AI initiatives with strategic goals. 
 
Stay on top of emerging trends in Generative AI, prompt engineering, and agent-based architectures. 
 
Define and advocate for best practices in model serving, integration patterns, and runtime efficiency-not just training ops. 
 
Preferred Qualifications 
 
Experience leading zero-to-one initiatives for AI product development 
 
Familiarity with synthetic data generation, fine-tuning techniques, and performance optimization for large models 
 
Understanding of agent-based interaction patterns, multi-agent communication protocols (e.g., MCP, A2A), and AG-UI concepts 
 
Prior work in designing user-facing AI features or tools; familiarity with frontend integration is a plus 
 
Excellent communication skills with the ability to translate technical concepts into business terms 
 
Ph.D. in Computer Science, AI, or related field, or equivalent industry experience with demonstrated impact in real-world applications 
 
Minimum Qualifications 
 
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 
 
1+ years plus of experience building AI-powered systems with a strong fundamental grasp of architecture and deployment 
 
Experience designing and delivering NLP or LLM-based systems, with knowledge of multi-modal and agentic AI frameworks 
 
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) 
 
Experience developing cloud platforms solutions (e.g., AWS, GCP, or public cloud, etc.) 
 
Hands-on experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex or similar), containerization (Docker, Kubernetes or similar), and scalable APIs 
 
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 . 
 
Pay &amp; Benefits 
 
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. 
 
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. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

AI Engineer, AI & Data Platforms (AiDP)

THRAD

<div><h3 class="jobSectionHeader">The Role</h3>
We are looking for an Applied Scientist to own the models that decide which ad appears in which AI conversation, in real time, across millions of queries a day. Ad selection inside LLM chats is a genuinely new problem: no click history, no cookies, no page context. Just an evolving conversation and a few hundred milliseconds to make a decision that has to feel native to the user, relevant to the advertiser, and profitable for the publisher.
This is a research role with a production mandate. Your models go live, not into a paper. You will work directly with our CTO and the founding engineering team on the systems powering millions of ads a day across Fortune 500 campaigns.<h3 class="jobSectionHeader">
Core Tech Stack</h3><ul><li>
ML: PyTorch, embedding-based retrieval, modern transformer architectures</li><li>
Backend: Python (FastAPI), async serving, real-time inference</li><li>
Data: PostgreSQL for transactional, ClickHouse for analytics and event data</li><li>
Infra: AWS, Docker, CI/CD</li><li>
Plus: whatever the problem demands. We pick tools that ship.</li></ul><h3 class="jobSectionHeader">
Example Projects</h3><ul><li>
Design and train contextual ad relevance models for LLM conversations, from retrieval through ranking through creative selection.</li><li>
Build efficient algorithms for real-time bidding and auction mechanics, balancing publisher yield and advertiser ROAS.</li><li>
Productionize regression models to predict downstream conversion from early conversational signals.</li><li>
Apply privacy-preserving clustering methods to categorize conversational context and improve advertiser targeting without compromising user data.</li><li>
Run live experiments against real traffic on our publisher network. Iterate on CTR, ROAS, and conversation quality metrics.</li><li>
Own the evaluation framework for ad quality, relevance, and user experience across the marketplace.</li><li>
Read an ArXiv paper on Monday. Have a prototype running on Friday.</li></ul><h3 class="jobSectionHeader">
What You Will Do</h3><ul><li>
Own the research and shipping of the models powering ad selection across Thrad's network.</li><li>
Move research to production end to end: hypothesis, training, evaluation, deployment, monitoring.</li><li>
Collaborate directly with the CTO and co-founders to translate research direction into working systems, often within the same day.</li><li>
Partner with the Data and Product teams to design and analyze live experiments on real traffic.</li><li>
Contribute to system architecture decisions as we scale from millions to billions of daily ad impressions.</li><li>
Communicate findings clearly to both technical and non-technical audiences across the team.</li></ul><h3 class="jobSectionHeader">
Who You Are</h3>
Must-haves<ul><li>
2 to 5 years of applied ML experience, ideally in ads, search, recommendations, ranking, or NLP.</li><li>
An advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field &mdash; or equivalent experience shipping production ML.</li><li>
Strong fundamentals in mathematical and statistical modeling. You know why your model works, not just that it does.</li><li>
Fluent in PyTorch, modern transformer architectures, and embedding-based retrieval.</li><li>
Strong Python, comfort with distributed training and inference.</li><li>
You have shipped ML to production at scale. Not just notebooks.</li><li>
You enjoy identifying and owning hard, open-ended problems. You form testable hypotheses and run them to ground.</li><li>
Based in San Francisco or willing to relocate. This is an in-person role at our SF HQ.</li></ul>
Nice-to-haves<ul><li>
Experience with RLHF, preference modeling, or LLM fine-tuning.</li><li>
Background in auction theory, bidding systems, real-time pricing, or yield optimization.</li><li>
Prior work at an ad-tech, search, recommendations, or marketplace company.</li><li>
Published research at NeurIPS, ICML, ACL, KDD, RecSys, or equivalent.</li><li>
Familiarity with ClickHouse or other column-oriented OLAP databases for analytical workloads.</li><li>
A relentless interest in the AI and LLM ecosystem and how advertising will evolve inside conversational interfaces.</li></ul><h3 class="jobSectionHeader">
Why Thrad</h3><ul><li>
First mover: We are defining a new category. Paid ads in AI is an inevitable market and we are building the infrastructure for it.</li><li>
Real traction: Fortune 500 clients, millions of daily impressions, and publisher partners across the AI web, all pre-seed.</li><li>
Research with teeth: Your work ships. Your models run in production against real traffic with real revenue on the line.</li><li>
Direct impact: Small founding team. Your decisions shape the models, the product, and the company.</li><li>
Ownership: Meaningful equity in a company at the intersection of two massive markets: AI and ad tech.</li><li>
Craft: A team that cares about shipping quality, not just quantity.</li></ul><h3 class="jobSectionHeader">
How to Apply</h3>
Send your CV and a brief note on what excites you about building at the intersection of AI and advertising. If you have published work, a GitHub, or models you have shipped that you are proud of, include them. We read every application.</div>

Applied Scientist

Explore 71+ Machine learning engineer in San Francisco this May. Find roles across top companies and apply now to boost your career.