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machine learning engineer

Stealth Startup

<div>
 
 The Culture We Are Building
 
 <ul>
 <li>
 We are assembling a lean group of generalists. While we welcome experience, we're primarily looking for creative, curious problem solvers with a keen interest in open-ended, technically challenging problems.
 </li>
 <li>
 We are looking to hire in-person in San Francisco. We believe that having a community is critical for learning, growth, and camaraderie. We will pay generously for relocation assistance.
 </li>
 <li>
 We want to invest heavily in our team's growth. We will happily sponsor conference attendance and encourage projects and research. If there's something that will help you grow as an engineer, researcher, or designer, we actively want to support it.
 </li>
 <li>
 We believe in compensating exceptional talent exceptionally well. We are an early stage company, but are committed to working with candidates we're excited about to ensure they are excited too.
 </li>
 <li>
 We have an academic as well as competitive spirit. We enjoy thought exercises, math puzzles, intellectual inquiry, and vigorous debates.
 </li>
 </ul>
 
 
 
 
 Role: Machine Learning Engineer
 
 
 Design, train, and ship models that guide reviewers to the most important changes, resolve merge conflicts more safely, and make diffs understandable through semantic grouping and summarization. You'll combine retrieval, code‑aware modeling, and small‑model techniques to deliver low‑latency, cost‑effective ML in production.
 
 
 Responsibilities
 
 <ul>
 <li>
 -Train and fine‑tune models that predict the next location a reviewer should focus on: ranking files, hunks, and comments
 </li>
 <li>
 -Build ML‑assisted merge conflict resolution: align and reconcile hunks using code context/AST, propose safe resolutions, and explain changes
 </li>
 <li>
 -Develop semantic change grouping and diff visualization: detect refactors/moves, cluster related edits across files, and generate concise summaries
 </li>
 <li>
 -Evaluate retrieval and RAG for pull requests: retrieve relevant context, discussions, and history to improve grouping, prioritization, and summarization
 </li>
 <li>
 -Design offline/online evaluation: labeled datasets, ranking metrics (e.g., MAP/NDCG), A/B experiments, and human‑in‑the‑loop feedback
 </li>
 <li>
 -Operate efficient inference: apply small‑model techniques (LoRA, supervised fine‑tuning, distillation, quantization)
 </li>
 </ul>
 
 Qualifications
 
 <ul>
 <li>
 -Strong background in deep learning research and implementation, with experience in modern architectures and concepts (transformers, MoE, reasoning, etc.)
 </li>
 <li>
 -Track record publishing results at top-tier conferences (NeurIPS, ICML, ICLR)
 </li>
 <li>
 -Expertise in Python and ML frameworks (PyTorch, JAX)
 </li>
 <li>
 -Experience with MLOps and model optimization (ONNX, TensorRT, serving infrastructure)
 </li>
 <li>
 -Familiarity with cost‑effective techniques: LoRA, supervised fine‑tuning, distillation, and quantization for small/efficient models
 </li>
 <li>
 -Familiarity with systems programming across the stack: Rust/C/C++, CUDA/GPU optimization, and kernel-level performance tuning
 </li>
 <li>
 -Experience with reinforcement learning, particularly in systems optimization and decision-making tasks
 </li>
 </ul>
 
 
</div>

Machine Learning Engineer [32985]

Handshake

<div><h1 class="jobSectionHeader">About Handshake</h1>
Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.
Why join Handshake now:<ul><li>
Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel</li><li>
Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world&rsquo;s top educational institutions</li><li>
Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others</li><li>
Build a massive, fast-growing business with billions in revenue</li></ul><h1 class="jobSectionHeader">
About the Role
</h1>Handshake is hiring an Associate Machine Learning Engineer for the Growth Relevance team. AI is transforming how students navigate their careers, and we're committed to providing innovative, responsible AI-powered solutions that guide students from educational aspirations to meaningful career opportunities. In this role, you will contribute directly to this mission by developing, deploying, and enhancing machine learning systems focused on lifecycle optimization, personalized notifications, and monetization strategies.
You'll join a high-impact team leveraging cutting-edge ML infrastructure, including embedding-based retrieval, Graph Neural Networks, and multi-stage rankers built upon a robust data platform with billions of data points. Your work will drive critical marketplace metrics, enhance user engagement, and contribute to responsible AI practices around explainability, fairness, and quality.
What You'll Do<ul><li>
Innovator: Develop and iterate on machine learning models and features that directly influence user experience across lifecycle, notifications, and monetization &mdash; with guidance from senior engineers.</li><li>
Collaborator: Partner with senior engineers, data scientists, and product managers to develop and iterate on machine learning models that improve product features and user experience.</li><li>
Learner: Grow your technical depth by working alongside experienced ML practitioners, picking up best practices in model development, experimentation, and production deployment.</li></ul><h1 class="jobSectionHeader">
Desired Capabilities
</h1><ul><li>Bachelor&rsquo;s degree in Computer Science, Data Science, or a related field</li><li>
0&ndash;2 years of experience in machine learning, data science, or a related area</li><li>
Proficient in Python, with hands-on experience in frameworks such as scikit-learn, PyTorch, or TensorFlow</li><li>
Strong foundation in core ML concepts, including classification, regression, ranking, and model evaluation</li></ul>
Extra Credit<ul><li>
Master&rsquo;s degree or currently pursuing an advanced degree in a relevant field</li><li>
Exposure to areas such as recommendations, personalization, NLP, deep learning, LLMs, or explainable AI</li><li>
Familiarity with the ML lifecycle (e.g., experiment tracking, model monitoring, feature pipelines)</li><li>
Experience with cloud platforms (GCP, AWS, or Azure)</li><li>
Clear communicator, able to translate technical work for diverse audiences</li><li>
Collaborative mindset with experience working cross-functionally with product, analytics, and engineering teams</li></ul><h1 class="jobSectionHeader">
Perks</h1>
Handshake delivers benefits that help you feel supported&mdash;and thrive at work and in life.
The below benefits are for full-time US employees.
Ownership: Equity in a fast-growing company
Financial Wellness: 401(k) match, competitive compensation, financial coaching
Family Support: Paid parental leave, fertility benefits, parental coaching
Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend
Growth: $2,000 learning stipend, ongoing development
Remote &amp; Office: Internet, commuting, and free lunch/gym in our SF office
Time Off: Flexible PTO, 15 holidays + 2 flex days
Connection: Team outings &amp; referral bonuses
Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.
Compensation Range: $115K - $144K</div>

Associate Machine Learning Engineer

Uber

<div>About the Role
 
 
The Marketplace Signals team at Uber is responsible for building and optimizing foundational marketplace signals that power user experiences and drive marketplace efficiency. Our team ensures that key signals-such as eyeball ETA, spinner time, and supply reliability indicators-are leveraged effectively across various Uber products and levers, enabling data-driven decision-making and seamless coordination across different business functions.
 
 
What You'll Do
<ul><li>Develop and optimize ML models to enhance key marketplace signals (e.g., ETA predictions, supply availability metrics, demand forecasts).
</li><li>Collaborate with cross-functional teams (Pricing, Matching, Driver Incentives, etc.) to ensure marketplace signals are effectively utilized.
</li><li>Improve operational efficiency by building a centralized, scalable system for marketplace signals that serves multiple use cases.
</li><li>Leverage cutting-edge ML techniques (deep learning, probabilistic modeling, reinforcement learning, etc.) to continuously refine marketplace signals.
</li></ul>Basic Qualifications
<ul><li>B.S. in Statistics, Mathematics, Computer Science, or Machine Learning
</li><li>2 years of experience in software engineering with an emphasis on data-driven methodologies, deep learning, and online experimentation
</li><li>Strong problem-solving skills, with expertise in ML methodologies
</li><li>Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems (e.g. ads tech, recommender systems)
</li><li>Experience in ML frameworks (e.g. Tensorflow, Pytorch, or JAX) and complex data pipelines; programming languages such as Python, Spark SQL, Presto, Go, Java
</li></ul>Preferred Qualifications
<ul><li>3+ years of experience in software engineering specializing in applied ML methods
</li><li>Experience in designing and crafting scalable, reliable, maintainable and reusable ML solutions using deep-learning techniques and statistical methods.
</li><li>Detail-oriented, ownership and truth-seeking mindset.
</li><li>Values and produces analytic evidence and insight, as well as applying them to improve technical solutions.
</li><li>Experience working in a cross-functional and/or cross-business projects, partnering with Product, Scientists, and cross-org leads to shape the team's strategies
</li>Master's degree in Computer Science, Engineering, Mathematics or related field 
<li>
</li></ul> 
 
For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Machine Learning Engineer II

Zendesk

<div><h2 class="jobSectionHeader">Job Description
</h2>The Enterprise Machine Learning team drives organizational value through scalable ML solutions and data-driven insights, fundamentally changing how business decisions are made. We collaborate closely with stakeholders, applying the latest advances in machine learning, deep learning, and large language models (LLMs) to create highly impactful outcomes. Our commitment is to advance the state of AI, statistical modeling, and robust system design to enhance and expand our core business capabilities.
<h2 class="jobSectionHeader">Location
</h2>San Francisco, CA or Austin, TX (Hybrid)
Schedule: This is a hybrid role requiring an average of 2 days per week in-office, or as otherwise determined by the hiring manager
<h2 class="jobSectionHeader">Role Overview
</h2>As a Machine Learning Engineer, you will serve as a technical and strategic member within the team, driving the development and deployment of advanced data science and machine learning solutions&mdash;particularly those harnessing LLMs and deep learning. You will architect and scale ML systems, foster effective cross-functional collaborations, and ensure that business value is embedded in every technical decision. Your business acumen allows you to translate complex analytical approaches into actionable insights and stakeholder-friendly narratives, strengthening partnership and adoption across the enterprise.
<h2 class="jobSectionHeader">Key Responsibilities
</h2><ul><li>Drive the design, development, and deployment of advanced ML and AI solutions, with an emphasis on large language models (LLMs), deep learning architectures, and sophisticated statistical modeling.
</li><li>Build scalable, robust data science systems&mdash;from data ingestion, data curation, data modeling to algorithm development, model deployment and monitoring&mdash;meeting enterprise-grade performance, reliability, and compliance standards.
</li><li>Act as a subject matter expert, collaborating with data scientists, ML engineers, analysts, and business stakeholders to understand needs, define requirements, and deliver practical solutions with measurable business impact.
</li><li>Effectively articulate complex technical concepts to non-technical partners, bridging gaps between technical teams and business operations for maximum results.
</li><li>Drive adoption of best practices in MLOps, including CI/CD pipelines, containerization, orchestration, observability, and reproducibility.
</li><li>Oversee and enhance the integrity, security, and compliance of all data science workflows and contracts.
</li><li>Stay abreast of the latest industry advancements in ML, LLMs, deep learning, cloud data engineering, and MLOps solutions (AWS, Kubernetes, Snowflake, etc.).
</li><li>Fostering technical excellence and ensuring alignment with business objectives.
</li></ul><h2 class="jobSectionHeader">What We&rsquo;re Looking For
</h2>Education &amp; Experience:
<ul><li>3+ years&rsquo; experience in Data Science, Machine Learning, or a related field
</li><li>BA/BS in Computer Science, Data Science, or related discipline (advanced degree is highly preferred)
</li></ul>Technical Expertise:
<ul><li>Deep expertise in statistical modeling, machine learning, and deep learning (including practical experience with LLMs and transformers)
</li><li>Strong programming skills (Python preferred; Java, Scala, or similar also valued)
</li><li>Proven ability to build and optimize scalable data science solution, end-to-end from data pipelines (dbt, Astronomer, Snowflake, AWS) to deployment and monitoring (Docker, Kubernetes, CI/CD, MLOps best practices)
</li><li>Experience handling and analyzing large datasets, with a preference for experience in cloud data warehouses (Snowflake)
</li></ul>Business Acumen:
<ul><li>Demonstrated success in translating business needs into analytical solutions, driving quantifiable impact
</li><li>Strong stakeholder engagement skills, with a track record of building trusted business partnerships and driving adoption of data science initiatives
</li></ul>Communication &amp; Collaboration:
<ul><li>Exceptional ability to simplify and communicate complex data science concepts to technical and non-technical audiences alike
</li><li>Experience working cross-functionally with engineers, analysts, and product leaders
</li><li>Steadfast commitment to continuous learning, collaboration, and fostering an inclusive, innovative team environment
</li></ul><h2 class="jobSectionHeader">Why You&rsquo;ll Thrive Here
</h2><ul><li>Opportunity to develop and scale of LLM and deep learning solutions with real-world business impact
</li><li>An environment that values innovation, ownership, and professional growth
</li><li>The chance to work on high-visibility, high-impact projects at scale alongside a passionate multidisciplinary team
</li></ul>The US annualized base salary range for this position is $206,000.00-$308,000.00. This position may also be eligible for bonus, benefits, or related incentives. While this range reflects the minimum and maximum value for new hire salaries for the position across all US locations, the offer for the successful candidate for this position will be based on job related capabilities, applicable experience, and other factors such as work location. Please note that the compensation details listed in US role postings reflect the base salary only (or OTE for commissions based roles), and do not include bonus, benefits, or related incentives.
Hybrid: In this role, our hybrid experience is designed at the team level to give you a rich onsite experience packed with connection, collaboration, learning, and celebration - while also giving you flexibility to work remotely for part of the week. This role must attend our local office for part of the week. The specific in-office schedule is to be determined by the hiring manager.
The intelligent heart of customer experience
Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love.
Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.
As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law.
Zendesk is an equal opportunity employer, and we&rsquo;re proud of our ongoing efforts to foster global diversity, equity, &amp; inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. We are an AA/EEO/Veterans/Disabled employer. If you are based in the United States and would like more information about your EEO rights under the law, please click here .
Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to peopleandplaces@zendesk.com with your specific accommodation request.</div>

Senior Machine Learning Engineer - Hybrid (San Francisco or Austin)

Software Engineer, Machine Learning

Capital One

<div>Distinguished Software Data Engineer
As a Distinguished Engineer at Capital One, you will be a part of a community of technical experts working to define the future of banking in the cloud.
You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Distinguished Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while driving towards strong technology solutions.
At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence, and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech, mentoring internal talent and actively recruiting to keep building our community.
Distinguished Engineers are individual contributors who strive to be diverse in thought so we holistically visualize the problem space. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. Distinguished Engineers will significantly impact our trajectory and devise clear roadmaps to deliver next generation technology solutions. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other material to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization.
We expect our Distinguished Engineers to be<ul><li>
Deep technical experts and thought leaders that help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices.</li><li>
Visionaries who challenge the status quo, collaborating on Capital One&rsquo;s toughest issues, to deliver on business needs that directly impact the lives of our customers and associates.</li><li>
Role models and mentors, helping to coach and strengthen the technical expertise and know-how of our engineering and product community.</li><li>
Evangelists, both internally and externally, helping to elevate the Distinguished Engineering community and establish themselves as a go-to resource on given technologies and technology-enabled</li></ul>
In this role, you will work with our Enterprise Data Platform team to drive design and architecture of Capital One&rsquo;s mission critical Data Platforms.<ul><li>
You will define and execute a bold technical strategy for a unified Data Product architecture, engineering high-scale solutions for standardized, well-governed data creation that serves as the bedrock for enterprise-wide AI readiness. By modernizing our foundational Business Data Catalog, you will transform how the organization discovers and consumes data, turning fragmented datasets into high-fidelity, machine-ready assets.</li><li>
You will act as the bridge between deep engineering and business impact, to institutionalize and drive the adoption of rigorous data standardization practices, ensuring that our data consumption layer becomes a competitive engine that enables the enterprise to innovate with speed and precision.</li><li>
You are a visionary builder who balances high-level architecture with &quot;hands-on-keyboard&quot; execution, designing resilient, multi-tenant distributed systems and event-driven patterns that redefine enterprise scale.</li><li>
As the authoritative expert in data consumption, you don't just advise&mdash;you build the proof-of-concepts and exploratory analyses that bridge the gap between abstract tech strategy and mission-critical, production-grade solutions.</li><li>
Beyond the code, you are a catalyst for growth, mentoring the next generation of world-class engineers and championing a culture of inclusive excellence and inner-sourcing.</li><li>
You command the technical depth to influence executive strategy and the hands-on credibility to lead the enterprise-wide shift toward modern, AI-ready technologies.</li></ul>
Basic Qualifications:<ul><li>
Bachelor&rsquo;s Degree</li><li>
At least 7 years of experience in data engineering</li><li>
At least 3 years of experience in data architecture</li><li>
At least 2 years of experience building applications in AWS</li></ul>
Preferred Qualifications:<ul><li>
Masters&rsquo; Degree</li><li>
9+ years of experience in data engineering</li><li>
3+ years of data modeling experience</li><li>
2+ years of experience with ontology standards for defining a domain</li><li>
2+ years of experience using Python, SQL or Scala</li><li>
1+ year of experience deploying machine learning models</li><li>
3+ years of experience implementing big data processing solutions on AWS</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $269,100 - $307,200 for Distinguished Data Engineer 

San Francisco, CA: $293,600 - $335,100 for Distinguished Data Engineer 

San Jose, CA: $293,600 - $335,100 for Distinguished Data Engineer 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div>

Distinguished Software Data Engineer

The Trade Desk

<div>The Trade Desk is a global technology company with a mission to create a better, more open internet for everyone through principled, intelligent advertising. Handling over 1 trillion queries per day, our platform operates at an unprecedented scale. We have also built something even stronger and more valuable: an award-winning culture based on trust, ownership, empathy, and collaboration. We value the unique experiences and perspectives that each person brings to The Trade Desk, and we are committed to fostering inclusive spaces where everyone can bring their authentic selves to work every day.

Do you have a passion for solving hard problems at scale? Are you eager to join a dynamic, globally- connected team where your contributions will make a meaningful difference in building a better media ecosystem? Come and see why Fortune magazine consistently ranks The Trade Desk among the best small- to medium-sized workplaces globally.

What we do

Our Software Engineers are end-to-end owners who have the opportunity to participate in many aspects of designing, building, and delivering data-focused products for our stakeholders.

At The Trade Desk, we believe in building the back-end infrastructure of our platform with a focus on quality at scale. This means whether we are building parts of our client-facing applications, internal custom solutions for our own team members, or model pipelines for bidding optimizations, we are making sure that we have infrastructure, development, and tools to do it right and efficiently.

Our system performs all day, every day serving global traffic. We build a distributed system in a highly collaborative environment, utilizing a broad range of technologies. Our back-end developers work on finding solutions to algorithmic, optimization and scale challenges in everything we do.

About the role:

The Trade Desk Software Engineers are best described as end-to-end owners.
<ul>
<li>You will participate actively in all aspects of product strategy &ndash; from designing, building, and delivering products for our clients.</li>
<li>We have dozens of individual, mission-focused teams working across a wide spectrum of technological challenges.</li>
<li>You will have the opportunity, depending on your interests and aptitude, to lead engineers that focus on building large-scale distributed systems coordinating thousands of servers in cloud and physical data centers around the world, petabyte-scale data challenges, machine learning, advanced visualizations, and interactive user interfaces &ndash; to name a few.</li>
<li>Software Engineers contribute to more than our product &ndash; they help build up our team. Through a combination of mentoring and technical leadership of local teams, you will make others better and raise the bar for those around you.</li>
</ul>
We are a global team with different backgrounds, experiences and perspectives. To complement this team, you will welcome ideas that are different from your own and be well-versed in building from common ground to value, seek out, and foster invisible and visible dimensions of diversity.

Who you are:

Our culture is much deeper than just having fun together (though, we do that well too...). We take pride in our engineers being trust-builders, generous givers, scrappy problem solvers, and gritty pursuers of excellence. You do not have to meet all the requirements below, but we believe that people who meet most of them will have a higher likelihood of succeeding in this role:
<ul>
<li>The ideal candidate will have 2 to 5 years of impactful hands-on software engineering experience</li>
<li>You are a strong communicator. You're able to collaborate cross functionally with data scientists and root cause pain points in their workflow.</li>
<li>You have a passion for improving the efficiency of others. The work you will do in Machine Learning Operations will have a big impact on both the data scientists and the data engineers in our organization.</li>
<li>Experience building large scale data pipelines with spark is a plus.</li>
<li>Experience building machine learning models is a plus.</li>
<li>You have a Bachelor's/Master's level degree in a computer-science or relevant engineering related field or equivalent experience. Not everyone has the same level of access to opportunities. What is most important to us is what and how you can contribute, which is why our consideration is not limited by the level of education you have.</li>
<li>You think beyond just the task at hand to deeply understand the 'why' behind what you &amp; your team are doing.</li>
<li>You are a driver. You will own technical milestones and projects in a ground-breaking and fast-paced environment, driving them from inception till completion. This includes task planning, individual code contribution, and code reviews.</li>
<li>You understand engineering fundamentals. At our scale, many off-the-shelf techniques and existing technologies (open source and enterprise) simply don't work.</li>
<li>You are able to work from first principles to evaluate solutions and adapt them to a unique environment.</li>
<li>You are a broadly skilled engineer, accustomed to developing web services.</li>
<li>You have experience building always-on systems, working across a variety of technologies and service layers.</li>
<li>You have a product-focused mindset.</li>
<li>You have the passion and ability to contribute to the process of discovering what will delight our clients and push forward one of the world's largest and most influential industries toward a vision of openness, transparency, and evidence-based decision-making.</li>
<li>You work with confidence and without ego. Our engineers have deep knowledge and exercise a high degree of leadership in their daily work.</li>
<li>You have strongly-held, defensible ideas, and advocate for what you believe is right.</li>
<li>You are also adept at identifying and evaluating trade-offs, willing to be proven wrong, and quick to walk through fire to support your fellow teammates.</li>
<li>You value, seek out, and foster diversity.</li>
</ul>
Variety of technical opportunity is one of the best things about working at The Trade Desk as a software engineer which is why we do not expect you to know every technology we use when you start. What we care about is that you can learn quickly and find solutions to complex problems using the optimum tools for the job. What you know is less important than how well you learn and innovate. We don't need engineers who know all the answers; we need engineers who can invent the answers no one has thought of yet, to the questions yet to be asked.

The Trade Desk does not accept unsolicited resumes from search firm recruiters. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of The Trade Desk. The Trade Desk is an equal opportunity employer. All aspects of employment will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
#LI-AD1<div>

As an Equal Opportunity Employer, The Trade Desk is committed to creating an inclusive hiring experience where everyone has the opportunity to thrive.

Please reach out to us at accommodations@thetradedesk.com to request an accommodation or discuss any accessibility needs you may require to access our Company Website or navigate any part of the hiring process.

When you contact us, please include your preferred contact details and specify the nature of your accommodation request or questions. Any information you share will be handled confidentially and will not impact our hiring decisions.</div></div>

Software Engineer II - Data Workflow

Explore 146+ Machine learning engineer in San Francisco this April. Find roles across top companies and apply now to boost your career.