Who is Recruiting from Scratch:

Recruiting from Scratch is a premier talent firm that focuses on placing the best product managers, software, and hardware talent at innovative companies. Our team is 100% remote and we work with teams across the United States to help them hire.

Title of Role: Machine Learning Engineer

Location: Washington, D.C. or Remote (U.S.-based)

Company Stage of Funding: Series C

Office Type: Remote

Salary: $150,000 – $215,000 + Equity (5,000 shares)

Company Description

Our client is a trailblazing, venture-backed AI startup dedicated to reshaping mission readiness and operational efficiencies through intelligent data exploration. Built on a decade of research and trusted by government and enterprise clients alike, the company transforms complex datasets into actionable insights—faster, smarter, and more intuitively than ever before.

They’ve developed an advanced AI platform that empowers users to tackle critical capability gaps in maintenance, cyber intelligence, supply chain optimization, and predictive analytics. With strong momentum and clear technical leadership, they are continuing to expand their elite AI engineering team.

What You Will Do

As a Machine Learning Engineer, you will be at the forefront of AI product innovation—bridging software engineering, machine learning, and data engineering to enhance scalable AI solutions.

You will:

• Lead and implement upgrades to core platform functionality to support advanced data applications.
• Optimize data access patterns and runtime performance to ensure scalable, high-performing systems.
• Build modular, reusable Python components using best-in-class software engineering practices.
• Collaborate closely with cross-functional teams including Data Scientists, Product Managers, QA, and Customer Success to deliver impactful AI-powered tools.
• Architect and deliver production-ready ML pipelines and workflows that handle complex data engineering challenges.
• Craft and enhance dynamic, insight-rich dashboards using a Python SDK and visualization tools.
• Engage in performance tuning, rigorous testing, and structured code improvements to raise the quality bar.
• Participate in product development, from technical ideation through to deployment and iteration.

Ideal Candidate Background

We're seeking engineers with a strong foundation in production-level machine learning and data engineering, coupled with excellent software development practices.

Must-Have Experience:

• 4+ years of experience as a Machine Learning Engineer, Software Engineer, or Data Engineer.
• Proven track record of deploying ML applications into production environments.
• Strong Python skills with the data stack (pandas, NumPy, scikit-learn, PyTorch, etc.).
• Experience working with big data technologies (e.g., Spark, Snowflake, Databricks).
• Experience designing, building, and maintaining scalable ML pipelines.
• Solid CI/CD experience and version control workflows (e.g., Git).
• Familiarity with task schedulers (Airflow, Prefect, etc.) and web frameworks (Flask, Django).
• Strong communication skills and ability to collaborate across functions.

Security Requirement:

Must be a U.S. Citizen and able and willing to undergo security clearance (but do not submit candidates who currently hold active clearance).

Preferred

• Background or familiarity with defense-related applications or national security use cases.
• Experience with Docker, Kubernetes.
• Familiarity with analytics in Cyber (e.g., PCAP, CVEs, cyber threat monitoring).
• Experience with logistics, supply chain, or maintenance prediction systems.
• Prior exposure to building SDKs or developer-facing tooling.

Compensation and Benefits

• Salary Range: $150,000 to $215,000 (Candidates above range will still be reviewed)
• Equity: 5,000 shares
• Work Policy: Fully remote, U.S.-based with flexible hours (Core: 10am–4pm ET)
• Schedule: 40-hour work week
• Benefits: Comprehensive medical, dental, and vision insurance; unlimited PTO
• Sponsorship: Visa sponsorship not available at this time
• Start Timeline: Ideally within 4–8 weeks
• Headcount Goal: Hiring 1–3 individuals for this position