Senior Machine Learning Engineer

Job Title: Senior Machine Learning Engineer

Compensation: $180,000 - $200,000 base + 10% bonus

Location: Fully Remote (United States only)

About the Company

We’re partnering with a fast-growing technology company building a modern operating system for small and mid-sized businesses in a large, historically under-digitized industry. With tens of thousands of active users and millions of transactions flowing through the platform every year, the company has become a critical piece of infrastructure for its customers - helping them manage everything from quoting and workflow management through to payments in a single cloud-based system.

As the platform continues to scale, the team is investing heavily in AI and machine learning to unlock new intelligent product capabilities powered by proprietary operational data.

The Role

As a Senior Machine Learning Engineer, you’ll work across the full ML lifecycle - from identifying opportunities and developing models through to deploying and operating production systems used by tens of thousands of real-world users. This is not an experimentation-only role. You’ll be building robust ML systems that directly impact how businesses operate day to day.

The environment is highly collaborative and product-focused. You’ll work closely with engineering, product, data science, and data engineering to design scalable systems that combine traditional machine learning approaches with emerging LLM and agent-based workflows.

What You’ll Do

• Design, build, and deploy machine learning systems in production environments
• Develop models across a range of techniques, including regression, classification, clustering, ranking, and recommendation systems
• Own the ML lifecycle from data exploration and feature engineering through to deployment, monitoring, and iteration
• Build intelligent product features using large-scale proprietary operational datasets
• Contribute to the development of AI agents and LLM-powered workflows integrated into core product experiences
• Design and maintain scalable ML infrastructure, including feature stores, model serving, and CI/CD pipelines
• Partner closely with product and engineering teams to translate real-world business problems into ML solutions
• Help shape the architecture, tooling, and best practices of a growing ML function

What You’ll Bring

• Ample applied machine learning experience in production environments
• Proven experience shipping ML models and systems beyond research or notebooks
• Strong Python skills with hands-on experience using frameworks such as PyTorch or TensorFlow
• Solid foundation in classical machine learning techniques (regression, classification, clustering, ranking, feature engineering, experimentation)
• Experience with modern MLOps practices, including model versioning, deployment pipelines, monitoring, and orchestration
• Strong SQL and experience working with large-scale structured datasets
• Exposure to NLP, LLM-based systems, or vector databases is a plus
• Experience in startup or high-ownership environments where ambiguity and autonomy are expected
• A collaborative mindset - low ego, high ownership, and strong cross-functional communication

About People In AI

People In AI is a specialist recruitment partner focused on building world-class AI, machine learning, and data teams. We work closely with high-growth companies - from ambitious startups to global technology leaders - helping them hire the engineers and researchers shaping the future of intelligent systems.