Senior Machine Learning Engineer–Field Engagement

Striveworks • Washington, DC

22h • $160,000 - $200,000 • Hybrid

About The Position

As a Senior Machine Learning Engineer–Field Engagement at Striveworks, you will work directly with customers during trials and early deployments of Chariot, the company’s AI product suite, which includes Chariot Core, Forge, and vertical solutions. You will own the technical journey from initial login to customer value by building integrations, pipelines, and configurations that help customers solve real problems with Chariot, and carry technical context from pilot through post-sale to support lasting adoption.

Between customer engagements, you may work on product improvements, platform enhancements, onboarding resources, technical documentation, blogs, and papers describing applications of the products or related research. The role works closely with customer engineering and machine learning teams, as well as Striveworks Product, Engineering, Sales, and Business Development teams.

The position offers a hybrid/on-site work environment near a customer site in the Washington, DC; Seattle, WA; or Raleigh-Durham, NC area. Travel of up to 25% is expected. The anticipated base pay range is $160,000–$200,000 per year. Total compensation includes base salary, equity grants, and cash bonuses.

Requirements

• Degree in a technical field such as computer science or engineering, or a similar field.
• At least 6 years of experience as an ML engineer, data scientist, forward-deployed engineer, or in a similar hands-on technical role; direct customer exposure is ideal.
• Strong technical fluency in AI and machine learning systems and ability to work across software engineering, data science, ML engineering, and infrastructure teams.
• Strong software engineering skills, including writing, reading, and debugging production-quality Python and building pragmatic integrations, prototypes, and tooling.
• Ability to work through ambiguity, independently understand problems, develop plans, and execute without detailed 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 higher US security clearance.

Nice To Haves

• 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 higher US security clearance.

Responsibilities

• Develop deep, hands-on expertise across Chariot Core, Forge, and vertical solutions, and run customer trials end to end.
• Lead hands-on customer onboarding, demonstrations, and workshops tailored to customer use cases; identify high-value problems and configure models, datasets, agents, and workflows to create working environments.
• Work with customer engineering and machine learning teams to design and build production AI systems and agents on Chariot, from prototype through rollout.
• Develop ETL pipelines, scripts, and custom integrations to ingest customer data and connect existing processes to inference endpoints.
• Serve as the primary technical point of contact during evaluations and early deployments; troubleshoot issues, remove technical blockers, and see problems through to resolution.
• Advise customers on architecture, implementation decisions, best practices, product capabilities, and roadmap directions; surface opportunities for deeper adoption and expansion to Sales and Business Development.
• Partner with Product and Engineering on high-value platform improvements needed during trials and support new feature launches with field perspective.
• Share field feedback with the Product team and create reusable assets such as example code, guides, documentation, and proof-of-concept templates.
• Between customer engagements, contribute to product and platform improvements, onboarding and technical resources, blogs, and technical papers.

Benefits

• Medical, dental, and vision insurance.
• Voluntary life, long-term disability, accident, and hospital indemnity insurance.
• HSA and FSA plans, including dependent care FSA.
• 401(k) plan.
• Unlimited PTO.
• Paid parental leave.
• Equity grants and cash bonuses as part of total compensation.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior