Machine Learning Engineer (Contractor)

Tech Holding

35d•Remote

About The Position

Working at Tech Holding isn't just a job, it's an opportunity to be a part of something bigger. We are a full-service consulting firm that was founded on the premise of delivering predictable outcomes and high-quality solutions to our clients. Our founders and team members have industry experience and have held senior positions in a wide variety of companies – from emerging startups to large Fortune 50 firms – and we have taken our combined experiences and developed a unique approach that is supported by the principles of deep expertise, integrity, transparency, and dependability. We are seeking a talented Machine Learning Engineer, for a project-based assignment, with 5+ years of experience to join our growing engineering team. In this role, you will design, build, and deploy machine learning models that power data-driven products and insights across the organization. You will work at the intersection of machine learning, data engineering, and scalable systems to deliver reliable and high-performing ML solutions.

Requirements

5+ years of professional experience in machine learning engineering or a related role.
Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.
Experience building, training, and deploying machine learning models in production environments.
Experience working with data pipelines and large-scale datasets.
Proficiency with cloud platforms (AWS, GCP, or Azure) and familiarity with MLOps practices.
Strong understanding of data structures, algorithms, and software engineering principles.
Experience with large-scale data processing frameworks (Spark, Dask, or similar).
Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field (or equivalent experience).

Nice To Haves

Experience working with natural language processing, computer vision, recommendation systems, or other applied ML domains.
Familiarity with model deployment, experiment tracking, and model monitoring tools.
Experience working with distributed systems and scalable ML infrastructure.
Exposure to modern techniques such as transformer architectures, embeddings, or large language models.
Experience working in a fast-paced startup or product-driven environment.

Responsibilities

Design, develop, and deploy machine learning models to solve business problems across large-scale datasets.
Build and optimize machine learning pipelines for data preparation, model training, and inference.
Collaborate with data engineers and software engineers to develop scalable ML infrastructure and pipelines.
Research and implement modern machine learning techniques, including deep learning and large language models where appropriate.
Work closely with product and cross-functional teams to translate business requirements into technical solutions.
Deploy and maintain machine learning models in production environments.
Monitor model performance, conduct experiments and A/B testing, and continuously improve model accuracy and reliability.
Contribute to the team's engineering best practices, including code reviews, documentation, and knowledge sharing.