Tech Holding is a full-service consulting firm focused on delivering high-quality solutions. They are seeking a talented Machine Learning Engineer to design, build, and deploy machine learning models that drive data-driven products and insights.
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
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)
- 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