Senior Machine Learning Engineer

Senior Machine Learning Engineer, Applied AI Systems

Compensation: $180K – $210K base + bonus

Location: Fully Remote (U.S. and Canada) (excluding Quebec)

About the Company

A rapidly growing SaaS platform transforming a large, underserved industry by bringing modern, cloud-based tooling to tens of thousands of businesses.

This company is building mission-critical software that powers day-to-day operations for a fragmented, historically under-digitized market. With a strong and expanding user base, they are now investing heavily in AI/ML to unlock the next phase of product innovation leveraging rich proprietary data to build intelligent systems that drive real-world impact at scale.

The Role

This is a high-impact, foundational hire within a newly forming AI/ML team. You’ll play a key role in designing and deploying production-grade machine learning systems that directly shape product capabilities.

This is not a research-only or API-wrapping role—you’ll own the full ML lifecycle, from problem definition and experimentation through to deployment and monitoring, working on both classical ML systems and emerging LLM/agent-based workflows.

What You’ll Do

* Design, build, and deploy end-to-end machine learning systems in production

* Develop models across regression, classification, clustering, ranking, and recommendation systems

* Build and optimize data pipelines, feature engineering workflows, and feature stores

* Collaborate cross-functionally with product, engineering, and data teams

* Contribute to MLOps practices including CI/CD, monitoring, and model lifecycle management

* Develop AI agents and LLM-powered workflows integrated into real product experiences

* Leverage large-scale structured datasets to build defensible, data-driven product features

* Help shape the technical direction and foundations of the ML function

What You’ll Bring

* 5+ years of applied machine learning experience (or equivalent depth)

* Proven track record of shipping ML systems into production environments

* Strong Python skills and experience with frameworks like PyTorch or TensorFlow

* Solid grounding in core ML concepts (feature engineering, evaluation, experimentation)

* Experience working with large-scale datasets and SQL

* Familiarity with modern MLOps practices (model serving, orchestration, monitoring)

* Exposure to NLP, LLMs, or vector databases is a strong plus

* Comfortable operating in ambiguous, fast-moving environments with high ownership

* Collaborative, low-ego mindset with strong communication skills

Tech Stack

* Python

* PyTorch / TensorFlow

* SQL & large-scale data systems

* Cloud infrastructure (AWS/GCP/Azure)

* Feature stores & MLOps tooling

* LLM frameworks and vector databases (where applicable)

Why Join?

* Work on real-world ML problems with meaningful production scale (tens of thousands of users, millions of transactions)

* Shape the foundation of an AI/ML function from an early stage

* Access to rich proprietary datasets in a largely untapped industry

* Blend of greenfield innovation and established product-market fit

* Opportunity to build both classical ML systems and next-gen AI/agent workflows

* Direct impact on how thousands of businesses operate and grow

About People In AI

People In AI partners with high-growth companies to build world-class AI and engineering teams. We focus on connecting exceptional talent with impactful opportunities across machine learning, data, and infrastructure always with a candidate-first approach.