We are looking for a talented and motivated Machine Learning Developer who brings together strong foundational skills in ML and Deep Learning, hands-on experience with Java or Python, and a solid understanding of big data pipelines such as Apache SparkThis role requires familiarity with batch processing, event streaming, and the application of Generative AI (GenAI) models in real-world scenarios.

Responsibilities

• Design, develop, and deploy machine learning and deep learning models using PyTorch, TensorFlow, or similar frameworks.
• Develop and integrate GenAI-based solutions such as large language models (LLMs) and text generation into production systems.
• Work with big data pipelines and event-driven architectures using Apache Spark and Kafka
• Collaborate with cross-functional teams to integrate ML/DL models into business applications.
• Handle preprocessing, feature engineering, and performance optimization for large-scale datasets.
• Conduct experiments, evaluate models, and iterate based on feedback and results.
• Ensure robustness, scalability, and maintainability of ML solutions in production.
• Monitor model behavior and data quality post-deployment.
  
  

Requirements

• Solid understanding of machine learning concepts and hands-on experience with ML algorithms.
• Proficiency in Java and/or Python for model development and data manipulation.
• Experience with deep learning frameworks such as TensorFlow or PyTorch.
• Hands-on experience with Generative AI techniques and foundational models.
• Strong grasp of Apache Spark for batch processing and Kafka for event streaming.
• Ability to work with large-scale, distributed data environments.
• Knowledge of data formats like Parquet, Avro, and optimization strategies for data storage and retrieval.
• Familiarity with model deployment workflows and versioning.
• Experience with ML lifecycle tools such as MLflow, Weights and Biases, or Kubeflow.
• Understanding of data lake technologies like Apache Iceberg or Delta Lake.
• Knowledge of containerization and orchestration using Docker and Kubernetes.
• Exposure to cloud environments (AWS/GCP/Azure) for model training and deployment.
• Familiarity with LLM fine-tuning, embeddings, and prompt engineering.
• Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related technical field.
  
  

This job was posted by Neha Kothari from Applicate IT Solutions.