ML Engineer

Catalyst Labs; California (MO); On-site; USD 80,000 - 120,000; Full time

Job summary

A leading talent agency in AI is looking for an ML Engineer to design, build, and deploy production-grade ML systems. This role offers full ownership of the model lifecycle, collaborating with teams to deliver impactful solutions. Candidates should hold a related degree and have experience with ML frameworks like PyTorch and TensorFlow. Strong programming skills in Python and excellent communication abilities are required. The position is full-time based in the US, focusing on innovative AI and audio ML applications.

Qualifications

• 1-6 years of professional experience in ML engineering.
• Hands-on experience with ML frameworks such as PyTorch or TensorFlow.
• Familiarity with cloud environments, preferably AWS.

Responsibilities

• Design, build, and deploy production-grade ML systems.
• Collaborate with cross-functional teams to shape the AI stack.
• Handle the entire AI lifecycle from data acquisition to monitoring.

Skills

Python

Machine Learning

Communication skills

Data pipeline design

Education

Bachelor’s or Master’s degree in Computer Science, Machine Learning, or AI

Tools

PyTorch

TensorFlow

AWS

FastAPI

Job description

Is a rapidly growing Tier 1 VC backed startup based in New York with $60 million in funding revolutionizing how outside sales and service teams work. Their AI technology captures and analyzes real-world conversations, providing full visibility into every customer interaction without the need for traditional ride-alongs.

By turning field conversations into searchable, actionable data, they empower teams to coach more effectively, close more deals, and boost average ticket sizes. Combining cutting-edge AI with a deep understanding of field sales dynamics, this company is redefining how businesses learn from and optimize their in-person customer experiences.

About Us

Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency that’s deeply embedded in our clients’ recruitment operations.

We collaborate directly with Founders, CTOs, and Heads of AI in those themes who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem-solving mindset, and long-term growth trajectory in the evolving world of intelligent systems.

Location

New York, NY

Work type

Full Time

Design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecycle from conception to deployment and maintenance.

Architect and deliver AI-powered solutions enabling natural speech interaction and real-time audio understanding.

Develop and optimize ML models focused on audio data to extract business-critical insights from previously unstructured voice data.

Build agents capable of operating natively on real-world audio inputs.

Collaborate with cross-functional teams to shape the foundations of the AI stack, improve tooling, and drive innovation in LLM and audio ML applications.

Work directly with customers to identify needs, gather feedback, and deliver impactful real-world solutions.

Handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments.

Participate in continuous improvement of the ML infrastructure and processes for scalability and performance.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

1-6 years of professional experience in ML engineering.

Strong programming skills in Python (TypeScript experience is a plus).

Hands‑on experience with ML frameworks such as PyTorch or TensorFlow.

Familiarity with cloud environments and infrastructure (preferably AWS).

Strong understanding of data pipeline design, real‑time inference, and model monitoring.

Excellent communication skills with the ability to engage directly with customers and stakeholders.

Core Experience

Proven experience building and deploying ML models into production environments.

Demonstrated ability to own the full model lifecycle from data ingestion and model development to deployment and monitoring.

Experience with audio-focused ML projects or similar domains involving unstructured data.

Proficiency in building scalable data pipelines for model training and evaluation.

Familiarity with FastAPI, OpenAI APIs, Baseten, LiteLLM, LiveKit, PostgreSQL, Redis, and S3 is a plus.

Solid grasp of ML systems architecture, feature engineering, evaluation strategies, and deployment best practices.