Senior Machine Learning Engineer–Field Engagement

Striveworks • Seattle, WA

1d • 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 access through customer value, building integrations, pipelines, and configurations that help customers solve meaningful problems. You will carry technical context from pilot through post-sale to help turn successful evaluations into lasting adoption.

You will develop hands-on expertise across the product suite, lead customer onboarding, demos, and workshops, and work with customer engineering and ML teams to build production AI systems and agents. The role also includes developing data pipelines and integrations, troubleshooting and resolving technical issues, advising on architecture and implementation, and partnering with Product and Engineering on platform improvements and feature launches. Between customer engagements, you may improve the product, create onboarding resources and reusable technical assets, and write technical blogs and papers about product applications or related research.

The role has a hybrid/on-site work environment near a customer site in the Washington, DC; Seattle, WA; or Raleigh-Durham, NC area, with travel expected up to 25% of the time.

Requirements

• A degree in a technical field such as computer science or engineering, or a similar field.
• At least 6 years of experience as a machine learning 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, with the ability to work 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.
• Ability to work with 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 the company’s vertical solutions, and run customer trials end to end.
• Lead hands-on onboarding, demos, and workshops tailored to customer use cases; identify high-value problems and configure models, datasets, agents, and workflows to establish a working environment.
• Work alongside customer engineering and machine learning teams to design and build production AI systems and agents, 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 customer evaluations and early deployments; troubleshoot issues, remove blockers, and own problems through resolution.
• Advise customers on architecture and implementation decisions, best practices, product capabilities, and roadmap directions.
• Surface opportunities for deeper adoption and expansion to Sales and Business Development teams.
• Partner with Product and Engineering on rapid platform improvements and support launches of new features 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 improvements, onboarding and technical resources, and technical blogs and 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