ML Engineer

Catalyst Labs; Seattle (WA); On-site; USD 100,000 - 130,000; Full time

Job summary

A rapid growth AI startup is seeking an ML Engineer in Seattle, WA. The role involves designing and deploying ML models and working directly with clients to optimize their data solutions. Candidates should hold a degree in Computer Science or related fields, possess 1–6 years of ML engineering experience, and have strong programming skills in Python. Experience with tools like PyTorch or TensorFlow and familiarity with AWS infrastructure are desired. Competitive full-time position with significant growth potential.

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 and infrastructure (preferably AWS).

Responsibilities

• Design, build, and deploy production-grade ML systems.
• Architect and deliver AI-powered solutions for natural speech interaction.
• Develop and optimize ML models to extract insights from audio data.

Skills

Strong programming skills in Python

ML frameworks (PyTorch, TensorFlow)

Understanding of data pipeline design

Excellent communication skills

Education

Bachelor’s or Master’s degree in Computer Science

Tools

AWS

FastAPI

OpenAI APIs

PostgreSQL

Redis

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 optimise their in‑person customer experiences.

About Us

Catalyst Labs is a leading talent agency with a specialised 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 optimisation to productised 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

Responsibilities

• 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 optimise 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.