Machine Learning Engineer

Job Type: Full Time
Job Location: United States
Company Name: Contextual AI

About the job

About the role

As a Member of Technical Staff specializing in Applied Research, you will work on state of the art research and applying that to production systems for RAG 2.0 (Contextual Language Models + Fine Tuning + Alignment).

What you’ll do

  • Work on and do research in state-of-the-art retrieval augmented language models as well as fine tuning and preference alignment.
  • Collaborate closely with ML researchers, product managers, and designers to understand requirements and translate them into technical solutions.
  • Integrate this research into the product through Software Development.
  • Architect and build scalable and efficient backend services, APIs, and databases to support the platform’s functionality and performance requirements.
  • Ensure seamless integration with machine learning models and pipelines, enabling efficient model deployment and management.
  • Collaborate with cross-functional teams to continuously improve the platform’s functionality, usability, and user experience.
  • Stay up-to-date with industry best practices, emerging technologies, and advancements in machine learning and software development.
  • Mentor and provide technical guidance to junior team members, promoting knowledge sharing and professional growth.

What we’re seeking

  • Bachelor’s degree in Computer Science, Software Engineering, or a related field. Master’s or PhD preferred.
  • Detailed knowledge of machine learning concepts and frameworks. Language Models and NLP experience is a plus.
  • Strong Proficiency in programming languages such as Python, JavaScript, or Java and in backend software development.
  • Experience with cloud platforms, such as AWS, Azure, or GCP, and familiarity with deploying applications on the cloud.
  • Strong problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment.
  • Excellent communication and interpersonal skills, with the ability to work closely with cross-functional teams.

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