Lead customer-facing machine learning engineering for Striveworks’ Chariot AI product suite, spanning pilots to durable adoption.

Develop deep, hands-on fluency across Chariot Core, Forge, and vertical solutions to run trials end to end and support credible product discussions
Drive fast time-to-value through hands-on onboarding, demos, and workshops tailored to each customer’s use case
Identify the highest-value customer problem and proactively bring it to working status by configuring relevant models, datasets, agents, and workflows
Co-build production AI systems and agents with customer engineering and ML teams, from initial prototype through rollout
Build ETL pipelines, scripts, and custom integrations to ingest customer data and connect their processes to Striveworks inference endpoints
Own the technical relationship during evaluation and early deployment by troubleshooting issues, removing technical blockers, and driving problems through resolution
Advise customers beyond initial deployment on architecture and implementation decisions, best practices, and relevant product capabilities and roadmap directions
Surface opportunities for deeper adoption and expansion for Sales and BD teams
Partner with Product and Engineering on high-value platform improvements needed for specific trials, and support launch activities for new features using field perspective
Feed field learnings back to Product, and build reusable assets such as example code, guides, documentation, and proof-of-concept templates

Degree in a technical field (computer science, engineering, or similar)
6+ years of experience as an ML engineer, data scientist, forward-deployed engineer, or similar hands-on technical role, ideally with direct customer exposure
Strong fluency in AI and ML systems and the ability to collaborate across software engineering, data science, ML engineering, and infrastructure teams
Strong software engineering skills, including writing, reading, and debugging production-quality Python, plus building pragmatic integrations, prototypes, and tooling
Comfort with ambiguity: independently understand problems, form a plan, and execute without step-by-step direction
Experience deploying AI models and agents at scale
Experience with AI model and agent evaluation, observability, or guardrails
Strong customer communication skills and ability to build trust with technical stakeholders
US citizenship and eligibility/willingness to obtain and maintain a Secret (or above) US security clearance

Work directly with customers during trials and early deployments of Chariot, spanning Chariot Core (AIOps platform), Forge (agentic harness), and vertical solutions
Own the technical journey from first log in to real value by building integrations, pipelines, and configurations that help customers solve meaningful problems
Carry technical context from pilot through post-sale support to help evaluations become lasting adoption
Use field learnings to shape high-value work between engagements, including platform improvements, better onboarding and technical resources, and technical blogs/papers focused on applications or research

Medical/dental/vision insurance
Voluntary life, long-term disability, accident, and hospital indemnity insurance
HSA and FSA (including dependent care FSA)
401(k) plan
Unlimited PTO
Paid parental leave

Washington, DC (hybrid)
Hybrid/on-site work near customer sites in Washington, DC, Seattle, WA, or Raleigh-Durham, NC areas
Travel up to 25% of the time

Anticipated base pay range: $160,000–$200,000/year
Total compensation includes competitive base salary, equity grants, and cash bonuses

Experience deploying large language models using vLLM
Familiarity with cloud infrastructure, Kubernetes, APIs, distributed systems, or modern data and ML platforms
Experience leading, managing, or mentoring small, cross-functional engineering teams
Active Secret (or above) US security clearance

Equal Opportunity Employer; does not discriminate based on protected characteristics or other non-merit factors
No tolerance for discrimination or harassment
Application accommodation support via [email protected]
Participating employer in the E-Verify program
Employment eligibility verification required upon hire

Senior Machine Learning Engineer–Field Engagement

Job Description