Hyderabad, Telangana, India
Information Technology
Full-Time
SalesCode.ai
Overview
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
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.
- 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.
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