Senior Machine Learning Engineer (6 Month Contract)

About Introhive

Introhive is an AI-powered SaaS platform designed to help organizations realize the full value of their relationships and underutilized data across their business to increase revenues, employee productivity and to improve customer experience management.

We’ve grown a lot since we began our journey in 2012, but our core mission remains the same – help B2B organizations capture and deliver Customer Intelligence to teams, when and where it matters most to find, win, and grow more business.

Introhive is the fastest growing B2B customer intelligence platform, recognized as a category leader in sales intelligence and data quality management software by G2 Crowd, a top 10 fastest growing technology company in Deloitte’s Fast 50 Awards three years in a row, and the MarTech 2020 Breakthrough Award winner for Best CRM Innovation.

Leading brands in Technology, Commercial Real Estate, Financial Services, Accounting, Legal and Consulting trust Introhive for sales enablement and relationship intelligence.

The Opportunity

We are seeking a Senior Machine Learning Engineer for a full-time, 6-month contract position, with the potential to convert to a permanent role. In this critical role, you will architect and optimize cutting-edge machine learning systems, lead the development of AI-driven applications, and drive strategic adoption of advanced technologies, including large language models (LLMs) and retrieval-augmented generation (RAG).

You’ll collaborate with cross-functional teams to build enterprise-grade AI infrastructure, guide MLOps strategy, and mentor peers. This is a unique opportunity to join a passionate team and work on high-impact, production-level AI initiatives.

Key Responsibilities

ML Architecture & AI Development

• Lead the design, architecture, and implementation of scalable ML platforms and AI infrastructure.
• Drive the development and integration of LLMs and generative AI applications, including prompt engineering, embeddings, and inference workflows.
• Develop robust APIs to serve ML models and LLMs across internal tools and customer-facing platforms.
• Architect and scale retrieval-augmented generation (RAG) solutions with vector search databases.
• Lead initiatives for AI agents and assistive tools while ensuring responsible AI practices and compliance.

MLOps & Data Engineering

• Build and manage end-to-end ML pipelines, incorporating automated model retraining, monitoring, and governance controls.
• Optimize real-time data ingestion pipelines and maintain high-performance feature stores in tools such as Snowflake and Postgres.
• Deploy ML workloads using containerized or serverless AWS architectures.
• Implement AI governance frameworks and ensure compliance with enterprise policies and industry best practices.

Technical Leadership 

• Provide mentorship and technical oversight to junior and mid-level engineers.
• Establish best practices, architecture standards, and roadmaps for scalable AI development across teams.
• Collaborate with engineering, product, and leadership stakeholders to align AI initiatives with business goals.

Qualifications

• Master’s or PhD in Computer Science, Artificial Intelligence, Data Science, or a related field preferred.
• 8+ years of relevant experience in ML engineering, ML infrastructure, or AI platform development.
• Proven experience leading ML strategies, AI adoption, or technical platforms at scale.
• Advanced proficiency with ML frameworks and libraries, such as LangChain, OpenAI, Hugging Face, and Snowflake Cortex.
• Deep experience working with LLMs, vector databases, and RAG architectures.
• Strong command of the AWS ML ecosystem (e.g., SageMaker, Bedrock, Comprehend).
• Expertise in building and automating scalable ML pipelines with observability and lifecycle monitoring.
• Familiarity with AI observability tools and advanced model optimization techniques.
• Strong SQL and data pipeline development experience using Postgres, Snowflake, and dbt.
• Deep understanding of ETL/ELT workflows, including support for streaming and real-time systems.
• Demonstrated ability to lead and mentor engineering teams and define ML architecture strategies.
• Strong cross-functional communication and the ability to clearly articulate technical concepts to various stakeholders.

Why Introhive?

We are one TEAM! We attract the best and brightest and we empower them. We value each other and do what it takes to make each other successful. We treat our customers and partners the same way. We embrace the power of unity, diversity, and collaboration in all that we do.