Head of Machine Learning & AI Engineer

PeopleConnect Staffing; United States; Remote; USD 200,000 - 215,000; Full time

Job summary

A leading company is seeking a Head of Machine Learning & Applied AI Engineering to drive AI model development and customer success. This remote role requires extensive experience in AI/ML, strong programming skills, and a track record of delivering solutions in production environments. The ideal candidate will have a Master's or PhD and experience in early-stage startups.

Qualifications

• 5–10+ years’ experience in AI/ML with leadership experience.
• Strong programming skills in Python, C++, or Java.
• Experience with TensorFlow, PyTorch, or scikit-learn.

Responsibilities

• Drive core AI model development and deployment efforts.
• Oversee the full ML project lifecycle from research to production.
• Mentor ML engineers and data scientists.

Skills

Python

C++

Java

TensorFlow

PyTorch

scikit-learn

Spark

Hadoop

AWS

GCP

Azure

Education

Master’s or PhD in a related field

Job description

Description

Head of Machine Learning & Applied AI Engineering

Location: Remote in USA only; periodic travel to Seattle, Bay Area for team and client meetings

Compensation: $200K - $215K upon funding

Our client is on a mission to transform how professional organizations, industry associations, and expert communities solve problems, deliver value, and engage their members. They believe that with the right blend of innovation, leadership, and technology, these communities can play an even more powerful role in shaping industries and society. They are building intelligent, human-centered solutions that help these organizations thrive—combining the promise of AI with a deep understanding of how people and communities work. Founded by experienced leaders in technology, product strategy, and go-to-market execution, they are ready to scale.

Reports To: Chief Technology Officer (CTO)

Team Size: 2–4 Product Managers/Analysts within the first 12 months, with cross-functional influence over design & data teams

The Head of Machine Learning & Applied AI Engineering is responsible for ensuring customer success from engagement through ongoing use, impact, and renewal. This leader will work closely with early customers to understand their context, challenges, needs, and use cases—ensuring the platform delivers maximum relevance, adoption, and transformative value. This is a foundational role, initially hands-on, later focusing on team-building and scaling, impacting customer delight, product-market fit, and renewal expansion.

The Head of Machine Learning & Applied AI Engineering is the technical leader driving core AI model development and deployment efforts. You will define and execute their AI and ML strategy, focusing on neuro-symbolic, human-in-the-loop applied vertical AI, and agentic AI ecosystems built on robust, scalable, state-of-the-art models. Responsibilities include overseeing the full ML project lifecycle—from research and prototyping to production deployment. As the senior-most ML engineer, you will mentor ML engineers and data scientists, fostering innovation in natural language understanding, knowledge graph reasoning, and reinforcement learning.

Ideal candidates have experience at organizations like OpenAI, Google Brain/DeepMind, Meta AI, Microsoft Research, Anthropic, or similar, or in advanced ML engineering roles at companies such as Netflix or Apple. Experience deploying ML in enterprise settings, especially with security, compliance, or on-prem deployments, is a bonus. Familiarity with human-in-the-loop ML or hybrid AI projects—combining rules with learning or incorporating human feedback—is highly desirable.

Qualifications/Requirements:

• 5–10+ years’ experience in AI/ML, including at least 5 years of hands-on building and deploying ML models, with leadership or technical lead experience.

• Strong programming skills in Python, with proficiency in C++ or Java.

• Recent experience with TensorFlow, PyTorch, or scikit-learn.

• Experience with distributed computing or big data tools like Spark or Hadoop.

• Experience with cloud platforms AWS, GCP, Azure, and handling scaling issues.

• Balanced expertise as both scientist and engineer—solid theoretical foundation in AI and practical coding skills.

• Track record of delivering AI solutions into production environments, understanding scaling, data quality, and performance monitoring.

• Early-stage startup experience is highly preferred.

• Team player with a hands-on, get-stuff-done attitude.

• Master’s or PhD in a related field, with contributions to publications or patents preferred, especially in applying research to practical problems.

• Citizen or Green Card Holder—unable to sponsor at this time.

Qualified candidates please send resume to Kar[email protected]