In this Senior Machine Learning Engineer–Field Engagement role, you will partner closely with Striveworks customers during Chariot trials and early deployments, translating field needs into working technical outcomes and long-term adoption.
Location and Compensation
- Location: Washington, DC (hybrid)
- Salary: USD 160,000 - 200,000 per year
What You Will Do
You will own the technical journey for customers from first log in through lasting value. During trials and early deployments of Chariot, you will build integrations and pipelines, co-build production AI systems and agents, and incorporate field feedback to strengthen products and platforms. Your work will connect customer goals to the capabilities of Chariot Core (AIOps platform), Forge (agentic harness), and Striveworks vertical solutions.
Key Responsibilities
- Develop hands-on expertise across the Chariot product suite, including Chariot Core, Forge, and vertical solutions, enabling you to run trials end to end.
- Help customers realize 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 relevant models, datasets, agents, and workflows.
- Co-build with customer engineering and ML teams to design and build production AI systems and agents on Chariot, from prototype to rollout.
- Create ETL pipelines, scripts, and custom integrations to ingest customer data and connect it to Striveworks inference endpoints.
- Act as the primary technical point of contact during evaluation and early deployment, troubleshooting directly and removing technical blockers through resolution.
- Advise customers beyond the initial deployment by supporting sound architecture and implementation decisions and establishing best practices based on relevant product capabilities and directions.
- Surface opportunities for deeper adoption and expansion that Sales and BD can pursue.
- Partner with Product and Engineering to deliver high-value platform improvements when trials require capabilities the product does not yet provide, and support launches with a field perspective.
- Scale learning by translating field feedback into product inputs and reusable materials such as example code, guides, documentation, and proof-of-concept templates.
Required Qualifications
- Education: Degree in a technical field (computer science, engineering, or similar)
- Experience: 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 across AI and ML systems, with the ability to collaborate effectively 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 operating with ambiguity by independently understanding problems, developing plans, and executing 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 the ability to build trust with technical stakeholders
- Security clearance: US citizenship and eligibility, with willingness to obtain and maintain a Secret (or above) US security clearance
Technologies
- Python
- ETL pipelines
- vLLM
- Kubernetes
- APIs
Additional (Not Required) Experience
- 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
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
What It’s Like at Striveworks
- Trust and respect with consistent, constructive candor
- Commitment to doing the work well
- Ownership mindset tied to collective results
- Valuing candidates who share these values
Work Environment and Travel
- Hybrid/on-site work environment near customer sites in the Washington, DC, Seattle, WA, or Raleigh-Durham, NC, area
- Travel expected up to 25% of the time
Compensation Details
- Anticipated base pay range: $160,000–$200,000/year
- Total compensation includes competitive base salary, equity grants, and cash bonuses
Equal Opportunity and Accommodations
Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks does not tolerate discrimination or harassment of any kind. For assistance or reasonable accommodation in the application process, contact People Operations at hr@striveworks.us.
E-Verify and Employment Eligibility
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 the E-Verify program.
