Senior Machine Learning Engineer–Field Engagement

Join Striveworks as a Senior Machine Learning Engineer–Field Engagement and work at the intersection of customer impact and production AI. This hybrid role near customer sites around Washington, DC, Seattle, WA, or Raleigh-Durham, NC is designed for engineers who enjoy hands-on deployment and close collaboration. You will help ensure trials become real adoption of Chariot, owning the technical journey from first login through lasting value.

What you’ll build

• Partner directly with customers during trials and early deployments of Chariot, which includes Chariot Core (AIOps platform), Forge (agentic harness), and vertical solutions.
• Own the technical path from evaluation to post-sale success by building integrations, data pipelines, and model and workflow configurations that start customers with a working environment.
• Carry field learnings forward to improve platform capabilities, supporting launches of new features with practical, on-the-ground feedback.
• Invest in high-value work between engagements, including polishing product rough edges, contributing to platform improvements, improving onboarding and technical resources, and writing technical blogs or papers connected to customer applications and research.

Responsibilities

• Become an expert across the Chariot product suite, developing hands-on fluency across Chariot Core, Forge, and vertical solutions so you can run trials end to end.
• Help customers reach value quickly through hands-on onboarding, demos, and workshops tailored to each customer’s use case.
• Identify the highest-value problem to solve and drive it to working status by configuring models, datasets, agents, and workflows.
• Co-build with customer engineering and ML teams to design and build production AI systems and agents from prototype to rollout.
• Develop ETL pipelines, scripts, and custom integrations to ingest customer data and connect existing processes to inference endpoints.
• Serve as the customer’s primary technical point of contact throughout evaluation and early deployment, troubleshooting issues, removing technical blockers, and owning resolution.
• Advise beyond initial deployment on architecture and implementation decisions, establishing best practices and explaining relevant product capabilities and roadmap directions.
• Surface opportunities for deeper adoption and expansion that Sales and BD teams can pursue.
• Partner with Product and Engineering to deliver fast-turnaround improvements when a trial needs something the product does not yet do, and support feature launches with field perspective.
• Scale learning across the organization by capturing field feedback and building reusable assets such as example code, guides, documentation, and proof-of-concept templates.

Requirements

• A degree in a technical field (computer science, engineering, or similar)
• 6+ years as an ML engineer, data scientist, forward-deployed engineer, or similar hands-on role, ideally with direct customer exposure
• Strong technical fluency in AI and ML systems across software engineering, data science, ML engineering, and infrastructure teams
• Strong software engineering skills, including the ability to write, read, and debug production-quality Python, and build pragmatic integrations, prototypes, and tooling
• Comfort with ambiguity: independently understand a problem, develop 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 and willingness to obtain and maintain a Secret (or above) US security clearance

Technologies

• Python
• ETL pipelines
• vLLM
• Kubernetes
• APIs

Benefits

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

Compensation

The anticipated base pay range is $160,000–$200,000/year. Striveworks also offers a total compensation package that includes equity grants and cash bonuses.

Work environment and travel

• Hybrid/on-site work environment near a customer site in the Washington, DC, Seattle, WA, or Raleigh-Durham, NC area
• Travel up to 25% of the time

About the team culture

• Trust-focused collaboration with consistent candor delivered kindly and constructively
• Ownership and accountability for collective outcomes
• Respectful teamwork and genuine pride in doing the work well

Equal opportunity and application support

Striveworks is an Equal Opportunity Employer. If you require assistance or a reasonable accommodation in the application process, contact People Operations at [email protected].

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and complete an employment eligibility verification form upon hire. Striveworks participates in E-Verify.