Machine Learning Engineer

• 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

• 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

Remote Work Opportunitity