Forward Deployed Engineer (Training)

Triwill Group; San Francisco, Northern (CA, KY); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Equity

Medical, dental, vision coverage fore

Flexible PTO

Parental leave

Fertility stipend

401(k) plan

Exposure to ML startups

Job summary

Baseten powers mission-critical AI inference for leading companies, and is seeking Front Deployment Engineers to work directly with top AI customers, owning outcomes from PoC to production. You will design workloads, frame problems, and ship robust solutions, spanning inference, post-training, and deployment systems.

You will shape evals, triage incidents, and build scalable internal tooling, while collaborating across multiple accounts to keep stakeholders aligned and drive product improvements

Qualifications

• Minimum 1-2 years of software engineering experience in large production systems.
• Experience debugging complex production issues using logs, metrics, and traces to root-cause problems in unfamiliar systems.
• Ability to own ambiguous technical problems, including triaging, making decisions under uncertainty, and knowing when to pull in other engineers.
• Interest in working directly with customers, understanding their problems, and influencing the product.
• Clear communication on complex technical topics to customers or leadership.
• Genuine curiosity about AI inference and training, and a drive to become an expert in the infrastructure powering it.
• Willingness to respond to customers outside regular hours and participate in an on-call rotation.
• Excitement about solving problems for some of the largest and fastest-growing companies running mission-critical AI workloads.

Responsibilities

• Act as each account's de facto CTO on Baseten, with final accountability for how their workloads are designed, run, and scaled.
• Take customer objectives from vague to shipped: frame the problem, define the spec and success criteria, build the PoC, and carry it through to production quickly, using the right tools for the problem.
• Design the evals and benchmarks that isolate where quality or performance falls short, then close the gap yourself, whether that means optimizing inference, improving the model through post-training, or reworking the eval itself.
• Be the first responder to mission-critical failures including triage, owning the fix directly or route to the owning team and stay accountable until it ships.
• Build internal systems so that each engagement is faster than the last. This includes tooling and automation for eval and deployment infrastructure, and the recipes and reference implementations that make the product more self-serve.
• Shape the product itself, channeling what your accounts need into the roadmap and shipping fixes and features into Baseten's codebase yourself.
• Do all of this across multiple accounts at once, sequencing the work, pulling in the right people at the right time, and keeping customers and internal stakeholders aligned on status and risk.

Skills

Software engineering

Debugging production issues

Customer interaction

Communication

AI infrastructure

On-call experience

Problem ownership

Tools

Kubernetes

Slurm

Ray

TensorRT-LLM

vLLM

PyTorch

JAX

Job description

ABOUT BASETEN

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products.

THE ROLE

Forward Deployed Engineers work directly with the largest and fastest-growing AI companies in the world, owning their technical outcomes on Baseten and taking on the hardest problems in serving and improving models at scale. The work spans the model lifecycle: inference, post-training, and the systems that tighten the loop between them.

• Act as each account's de facto CTO on Baseten, with final accountability for how their workloads are designed, run, and scaled.
• Take customer objectives from vague to shipped: frame the problem, define the spec and success criteria, build the PoC, and carry it through to production quickly, using the right tools for the problem.
• Design the evals and benchmarks that isolate where quality or performance falls short, then close the gap yourself, whether that means optimizing inference, improving the model through post-training, or reworking the eval itself.
• Be the first responder to mission-critical failures including triage, owning the fix directly or route to the owning team and stay accountable until it ships.
• Build internal systems so that each engagement is faster than the last. This includes tooling and automation for eval and deployment infrastructure, and the recipes and reference implementations that make the product more self-serve.
• Shape the product itself, channeling what your accounts need into the roadmap and shipping fixes and features into Baseten's codebase yourself.
• Do all of this across multiple accounts at once, sequencing the work, pulling in the right people at the right time, and keeping customers and internal stakeholders aligned on status and risk.

QUALIFICATIONS

• Minimum 1-2 years of software engineering experience, shipping and maintaining code in large production systems, ideally with breadth across the stack
• Experience debugging complex production issues - working through logs, metrics, and traces to root-cause problems in unfamiliar systems
• Confidence owning ambiguous technical problems. This includes triaging, making decisions under uncertainty, and knowing when to pull in other engineers who own the underlying systems
• Motivation beyond pure engineering. An interest in wanting to work directly with customers, understand their problems firsthand, and influence the product
• Clear communication on complex technical topics, whether you're talking to a customer's engineers or their leadership
• Genuine curiosity about AI inference and training, and a drive to become an expert in the infrastructure powering it
• Willingness to respond to customers outside regular working hours and participate in an on-call rotation
• Excitement about solving problems for some of the largest and fastest-growing companies in the world running mission-critical AI workloads

WHAT YOU'LL BRING

• Depth in a core infrastructure domain such as storage systems or networking (anywhere from the cloud layer to cluster interconnects like InfiniBand and RoCE)
• Experience operating distributed compute platforms like Kubernetes, Slurm, or Ray, especially for GPU workloads
• A detailed understanding of LLM architectures and modern inference engines like vLLM, TensorRT-LLM, or SGLang
• The ability to profile and optimize GPU workloads, in training or serving
• Hands-on experience with post-training techniques like SFT and RL, or a broader deep learning background plus fluency in a tensor computation library like PyTorch or JAX
• Operational depth - running on-call, leading incident response, debugging distributed systems under pressure

BENEFITS

• Competitive compensation, including meaningful equity.
• 100% coverage of medical, dental, and vision insurance for employee and dependents
• Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
• Paid parental leave
• Fertility and family-building stipend through Carrot
• Company-facilitated 401(k)
• Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).