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’re looking for a skilled and motivated Machine Learning Engineer to join our innovative team on a full-time, 6-month contract, with the possibility of extension or transition to a permanent role. This is an exciting opportunity to design and deploy cutting-edge machine learning systems across production environments, leveraging advanced frameworks like LangChain, AWS Bedrock, PyTorch, and TensorFlow. If you’re passionate about building intelligent solutions and delivering business value through AI and MLOps, we want to hear from you.

Key Responsibilities

• Design, build, and maintain end-to-end ML pipelines, including data ingestion, feature engineering, model training, and deployment.
• Integrate and serve ML/LLM models through APIs to enable real-time applications.
• Collaborate with engineering teams to optimize data pipelines using tools like Snowflake, dbt, Ruby, and Postgres.
• Develop Retrieval-Augmented Generation (RAG) architectures using vector databases to support intelligent applications.
• Contribute to MLOps infrastructure by implementing CI/CD pipelines and automated testing and monitoring of models in production.
• Deploy and integrate ML solutions into customer-facing tools and enterprise systems.
• Apply relationship intelligence concepts, including entity resolution, CRM data analysis, and recommendation systems.
  

Qualifications

• Bachelor’s or Master’s Degree in Computer Science, Machine Learning, Data Science, or a relevant field.
• 2–4 years of professional experience in machine learning engineering, MLOps, or software engineering focused on AI/ML systems.
• Proven experience with Python and PySpark for building scalable data and machine learning solutions.
• Hands-on experience with modern AI frameworks and tools such as LangChain, AWS Bedrock, Hugging Face, TensorFlow, and PyTorch.
• Strong understanding of SQL, Snowflake, and data engineering best practices.
• Experience with deploying models using AWS ML services (SageMaker, Comprehend, Personalize) and serving tools such as TensorFlow Serving or TorchServe.
• Familiarity with CI/CD pipelines and best practices for model release management and monitoring.
• Comfortable working in a fast-paced environment where you can take ownership of complex problems and drive innovation.
  

Preferred Experience:

• Experience with RAG architectures and vector search implementations.
• Exposure to CRM platforms and relationship intelligence solutions.
• Background in deploying LLMs and generative AI use cases.
  

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.