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Protech Talent

Machine Learning Engineer

Hybrid

New york city, United states

$ 350,000 /year

Fresher

Full Time

09-12-2025

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Skills

Communication Problem Solving Python TypeScript PostgreSQL Stripe Kubernetes Monitoring Research Training Motivation Architecture PyTorch TensorFlow Autonomy react AWS OpenAI Full-Stack Development

Job Specifications

Applied AI Engineer

Full-time | Hybrid | New York City

Compensation: $150K – $350K + Competitive Equity

About the Role:

We’re looking for an Applied AI Engineer to help turn cutting-edge machine-learning research into production-grade, revenue-driving products.

You’ll own projects end-to-end — from model selection and data pipelines to deployment, monitoring, and iteration in live environments. Expect full autonomy, high accountability, and constant cross-functional collaboration with product and operations teams.

About the Company:

This company is a fast-growing AI-driven healthcare startup on a mission to make life-changing therapies accessible faster and more affordably. They’re combining first-party healthcare data with cutting-edge AI to streamline one of the most complex and outdated systems in the world — from insurance to drug access to patient support.

Backed by top-tier investors (including funds behind companies like Stripe, OpenAI, and Airbnb), they’re scaling rapidly and have already achieved strong product-market fit. The team is composed of exceptional engineers, operators, and scientists from top startups and research labs.

The culture is intense, collaborative, and ownership-driven — ideal for builders who thrive in zero-to-one environments and want to see their work make a measurable impact on real lives.

What you’ll do:

Build and productionize ML and LLM-based systems that power automation, prediction, and intelligent search.
Combine techniques like data extraction, document classification, workflow orchestration, and multimodal modeling.
Lead zero-to-one experiments and deliver models that ship to real customers.
Collaborate directly with business and engineering stakeholders to scope, design, and deploy AI-driven features.
Evaluate new methods, fine-tune models, and continuously improve reliability, latency, and accuracy.
Build internal tools and pipelines that accelerate future AI development.

This is a Hybrid, high-ownership position for builders who thrive in fast-moving, product-driven environments.

What We’re Looking For:

Experience

1–15 years as an AI / ML Engineer, Applied Scientist, or ML Research Engineer
Hands-on experience building and deploying ML systems in production (not research-only)
Background at a top-tier tech or early-stage startup that has shipped AI-powered products
End-to-end project ownership — data, training, infra, deployment, iteration

Technical Skills

Proficiency with modern ML frameworks (PyTorch, TensorFlow, Transformers, LLM APIs)
Experience fine-tuning, prompting, or orchestrating large-language-model systems
Strong foundation in full-stack development (Python + React / TypeScript / PostgreSQL / Kubernetes)
Comfortable designing scalable data and inference pipelines on cloud (AWS preferred)

Soft Skills

Low-ego, high-ownership mindset
Strong written + verbal communication and cross-team collaboration
Bias toward speed, clarity, and tangible results

Nice to Have

Founder or early-startup experience
Pear Fellow / Neo Scholar background
Degree in CS or related field from a top program (or equivalent practical excellence)

Why Join:

Product-market fit + hypergrowth: the platform already serves thousands of users and is scaling fast.
AI-first mission: core business outcomes are directly driven by applied ML and generative AI.
Top-tier funding + team: backed by leading investors; small, elite engineering org where impact compounds quickly.
High autonomy + ownership: you’ll shape not just the product but the AI infrastructure

Interview Process:

Initial Screen (30 min): Background, motivation, and alignment with company mission.
Technical Interview (45 min): Coding-focused (Python), similar to a Leetcode-style exercise.
Project Walkthrough (45 min): Deep dive into a previous ML or AI system you’ve built.
Systems Design (45 min): Evaluate how you approach scaling, deployment, and architecture.
Onsite / Final Round (Half Day): Collaborative project with the team to assess real-world problem solving and communication.

About the Company

Building teams and transforming careers is what we do. Whether you need to find the right fit for your team or the right step for your career we are here to help. With extensive experience across the German, UK and US markets in Tech, Commercial and Crypto roles, Protech holds integrity and a high level of service delivery at the core of everything we do. Want to find out more? Please reach out: +4420 38000 309 matt@protech-talent.com Know more