Your primary responsibilities will include designing and driving projects in the responsible AI frontier to identify, avoid, and mitigate bias across a wide range of ML applications at Pinterest. You'll collaborate with other engineering teams to leverage their platforms and signals and work with them to collaborate on the adoption and evaluation of Responsible AI practices and ML Fairness tooling across Pinterest.

You'll also mentor junior engineers on the Responsible AI team and across the company on the R-AI space, and work with the team and senior leaders at the company to define and drive technical strategy in this area.

To be successful in this role, you'll need extensive, real-world experience applying advanced ML methods to production systems, with a strong track record in responsible technology spanning fairness, ethics, and broader societal considerations. You'll also need deep familiarity with cutting-edge ML architectures and their applications in large-scale Search and Recommender Systems.

In addition, you'll need proven ability to measure, deploy, and refine fairness interventions and broader Responsible AI solutions at scale, bridging state-of-the-art research with tangible product impact. You'll also need 4+ years working experience in the engineering teams that build large-scale ML-driven user-facing products, and 1+ years experience leading cross-team engineering efforts.

Nice to have: publications at top ML conferences, experience using AI coding assistants, familiarity with LLM-powered productivity tools, and expertise in scalable real-time systems that process stream data.

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Key Responsibilities:

• Shape the direction of our applied AI areas and intelligence features in our products.
• Drive the development and deployment of state-of-the-art AI models and systems that directly impact the capabilities and performance of Databricks' products and services.
• Develop novel data collection, fine-tuning, and LLM technologies that achieve optimal performance on specific tasks and domains.
• Design and implement ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation and iteration.
• Work closely with cross-functional teams, including AI researchers, ML engineers, and product teams, to deliver impactful AI solutions that enhance user productivity and satisfaction.
• Build scalable, reusable backend systems to support GenAI products across the company.

What We’re Looking For:

• 2-8 years of machine learning engineering experience in high-velocity, high-growth companies.
• Strong track record of working with language modeling technologies.
• Proficiency in Python, TensorFlow/PyTorch, and scalable ML architectures.
• Ability to drive end-to-end model development, from research and prototyping to deployment and monitoring.
• Strong analytical and problem-solving skills, with a passion for improving AI-driven user experiences.
• Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment.

Why Join Us?

At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts.

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range for this role is $190,000-$285,000 USD.

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Location

San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $295K – $555K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team

Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference.

About the Role

We are looking for an engineer who wants to take the world's largest and most capable AI models and optimize them for use in a high-volume, low-latency, and high-availability production and research environment.

In this role, you will:

• Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production.

• Work alongside researchers to enable advanced research through awesome engineering.

• Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack.

• Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues.

• Optimize our code and fleet of Azure VMs to utilize every FLOP and every GB of GPU RAM of our hardware.

You might thrive in this role if you:

• Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference.

• Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done.

• Have at least 5 years of professional software engineering experience.

• Have or can quickly gain familiarity with PyTorch, NVidia GPUs and the software stacks that optimize them (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink, etc.

• Have experience architecting, building, observing, and debugging production distributed systems. Bonus point if worked on performance-critical distributed systems.

• Have needed to rebuild or substantially refactor production systems several times over due to rapidly increasing scale.

• Are self-directed and enjoy figuring out the most important problem to work on.

• Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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