Machine Learning Engineering Internship

STRATIVIS

9d•Remote

About The Position

STRATIVIS is a boutique HR consultancy and search firm partnering with high-growth companies to build exceptional teams. We combine executive search, talent advisory, and fractional HR leadership to help scaling organizations solve people-related problems smarter and faster. We move quickly, stay honest, and never lose sight of the details that matter. As we continue to evolve our internal capabilities, we’re investing in intelligent systems that streamline how work gets done, and that’s where you come in. We’re looking for a Machine Learning Engineering Intern to join us for a 12-week, part-time engagement (30 hours/week). This is a paid, fully remote role based in the U.S. This isn’t a typical internship. You’ll work on a high-impact, greenfield project: designing and building agentic tools to automate workflows across our HR consulting and recruiting operations. Think LLM-powered assistants, task automation pipelines, and intelligent systems that reduce manual effort and improve decision-making. You’ll operate with a high degree of ownership and autonomy — ideal for someone who thrives in fast-paced environments and is excited to build, experiment, and ship quickly.

Requirements

Currently pursuing or recently completed a degree in Computer Science, Machine Learning, Data Science, or a related field.
Hands-on experience with Python and common ML/AI tooling (e.g., PyTorch, TensorFlow, scikit-learn, or similar).
Familiarity with LLM ecosystems (e.g., OpenAI APIs, LangChain, vector databases, prompt design).
Strong problem-solving skills and comfort working with ambiguous requirements.
Ability to move quickly from idea to prototype to production-ready solution.
Excellent communication skills and the ability to explain technical concepts clearly.
Highly self-motivated: you take initiative, seek ownership, and don’t wait for direction.
Comfort working independently in a remote, fast-paced, startup-like environment.

Responsibilities

Build intelligent systems: Design and develop agent-based tools to automate core business workflows (e.g., candidate sourcing, data enrichment, reporting, internal ops).
Prototype rapidly: Translate ambiguous problems into working ML/AI solutions using modern frameworks and APIs.
Work with LLMs: Implement prompt engineering, orchestration, and evaluation techniques to improve system performance.
Collaborate directly: Partner with STRATIVIS leadership to identify high-leverage use cases and iterate quickly.
Ship and refine: Continuously test, improve, and scale solutions based on real-world usage and feedback.
Operate independently: Manage your time, priorities, and deliverables in a highly autonomous environment.