AI/ML Engineer

The Role

You are the engineer who ships. Your job is to take well-defined problems and produce working AI/ML systems that hold up in production. You will work closely with our Solutions Architect on architectural direction, but you will own the execution — writing code, training models, building pipelines, and delivering systems that work.

This role suits engineers who measure themselves by what gets shipped and how well it performs. You will have technical leadership above you to lean on for architectural calls, and substantial autonomy on the day-to-day work. Strong execution discipline matters more here than architectural creativity — though we expect you to bring both.

What You’ll Do

• Build and ship AI/ML systems across a range of problem types: predictive models, generative AI applications, NLP pipelines, anomaly detection, agentic systems.
• Own end-to-end execution on assigned scope: data engineering, model development, evaluation, deployment, and monitoring.
• Test, harden, and contribute to the launch of internal AI/ML product platforms.
• Operate the production AI/ML infrastructure that supports our work — model serving, inference pipelines, MLOps tooling — as a first-class part of the engineering job.
• Collaborate with the Solutions Architect on technical design, code review, and architectural decisions.
• Document your work clearly enough that someone else could pick it up six months from now.

What We’re Looking For

Required

• 5+ years of professional software engineering experience, with at least 3 years focused on AI/ML systems in production.
• Strong individual execution — you have shipped real ML systems that ran in production and produced measurable outcomes.
• Solid generalist range across the AI/ML stack: model development, evaluation, data engineering, deployment, and inference.
• Proficiency with Python, modern ML frameworks (PyTorch, Hugging Face, scikit-learn), and SQL.
• Experience with at least one major cloud platform and modern deployment patterns (containers, CI/CD, infrastructure as code).
• Comfort working in a small team where the lines between roles blur — you will sometimes write infrastructure code, sometimes do data engineering, sometimes ship a frontend integration.

Bonus

• Depth in one specialized area: computer vision, NLP / generative AI, time-series forecasting, or MLOps.
• Experience with LLM-based applications, agentic systems, or RAG pipelines.
• Background in productizing AI/ML systems — not just delivering models, but making them reliable, maintainable, and useful.
• Prior experience at a startup or small engineering team where you owned end-to-end systems.

About Vector-SG

Vector-SG is an AI/ML engineering firm building production systems that solve real, messy problems. We work where modeling meets the constraints of the real world: imperfect data, operational systems with consequences, users who need answers they can act on. Our team is small, technically deep, and intentional about who we hire.

We care about engineers who ship — people who can take an ambiguous problem, design a credible solution, and produce something that actually works. We value clear thinking over credentials, evidence over opinion, and the discipline to build things that hold up under scrutiny.

What You’ll Get from Working Here

• Real ownership of meaningful technical work, with the autonomy to make architectural decisions and the responsibility that comes with them.
• A small team of senior people who care about craft. No layers, no theater, no busywork.
• Hard problems that exercise the full range of modern AI/ML engineering — not toy datasets or proofs-of-concept that never ship.
• Direct exposure to product strategy, customer outcomes, and the business decisions that shape what gets built and why.
• A senior technical lead invested in your growth, with substantive code review and architectural mentorship.
• End-to-end ownership of real systems, not slices of someone else’s architecture.
• Competitive compensation, full benefits, and a hybrid work model anchored in the Woodbridge, VA area.

How We Work

Hybrid, with weekly in-person collaboration anchored in our Woodbridge, VA area. Some travel may be required for specific engagements (typically less than 10%), with advance notice and reasonable accommodation.

We default to small teams, short feedback loops, and writing things down. We prefer engineers who push back when they disagree, who ask for context before they build, and who finish what they start. We don’t do performance theater, status meetings without decisions, or process for its own sake.

Vector-SG is an equal opportunity employer. We hire based on capability, judgment, and fit — nothing else.

Pay

$103,171.89 - $124,250.02 per year

Benefits

• 401(k)
• 401(k) matching
• Dental insurance
• Flexible schedule
• Health savings account
• Retirement plan

Work Location

Hybrid remote in Woodbridge, VA 22192