Senior Software Engineer I

JOB DESCRIPTION:

This role involves collaborating with data engineers and data scientists to integrate generative AI solutions into our production environment. The ideal candidate will have a strong background in machine learning operations, software engineering, and a passion for building/deploying scalable AI solutions, including RAG and LLM-based systems.

Responsibilities:
· Design, develop, and implement MLOps pipelines for the continuous integration and deployment of generative AI models.
· Collaborate with data engineers to ensure seamless data flow and integration for AI model training and deployment.
· Work closely with data scientists to understand model requirements and optimize deployment processes.
· Automate the training, testing, and deployment processes for generative AI models.
· Monitor and maintain AI models in production, ensuring optimal performance, accuracy, and reliability.
· Implement best practices for version control, model reproducibility, and governance.
· Optimize machine learning pipelines for scalability, efficiency, and cost-effectiveness.
· Troubleshoot and resolve issues related to model deployment and performance.
· Ensure compliance with security and data privacy standards in all MLOps activities.
· Stay up-to-date with the latest MLOps tools, technologies, and trends.
· Provide support and guidance to other team members on MLOps practices.

Technical Skills:
· Programming Languages: Proficiency in Python, Scala, and SQL.
· Machine Learning Frameworks: Experience with Databricks MLflows, TensorFlow, PyTorch, and Scikit-learn.
· Automation Tools: Proficiency with Jenkins, Git, and Docker.
· Cloud Platforms: Experience with AWS, Azure (preferred) and their respective machine learning services.
· Containerization and Orchestration: Knowledge of Docker and Kubernetes.
· Data Engineering Tools: Familiarity with Apache Spark/ Databricks Spark (preferred), Kafka, and ETL processes.
· Version Control: Proficiency in using Git.
· Monitoring Tools: Experience with Prometheus, Grafana, or similar tools.
· CI/CD Pipelines: Knowledge of CI/CD best practices and tools.
· Security and Compliance: Understanding of security best practices and data privacy regulations.
· RAG and ALLM Development:
· RAG Solutions: Experience in developing RAG solutions, including designing data pipelines for document ingestion, chunking, enrichment, embedding, and retrieval. Familiarity with tools like LangChain and LlamaIndex for building RAG applications
· ALLM Solutions: Proficiency in integrating advanced large language models (ALLMs) into production environments. Knowledge of optimizing LLMs for specific tasks, managing model lifecycle, and ensuring efficient resource utilization.

Qualifications:
· Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
· 3-5 years of experience in MLOps, DevOps, or a related field.
· Strong understanding of machine learning principles and model lifecycle management.
· Hands-on experience with automated testing and deployment of machine learning models.
· Experience working in an Agile/Scrum development process.
· Excellent problem-solving skills and ability to troubleshoot complex issues.
· Strong communication and collaboration skills.

Good to have skills:-

•        Experience in Spark, Hadoop

•        Experience with MAVEN, Spring, XML, Tomcat

•        Experience in Unix and shell scripting and SQL server.

•        Experience with source code version control systems like GIT

Qualifications:
· Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
· 3-5 years of experience in MLOps, DevOps, or a related field.
· Strong understanding of machine learning principles and model lifecycle management.
· Hands-on experience with automated testing and deployment of machine learning models.
· Experience working in an Agile/Scrum development process.
· Excellent problem-solving skills and ability to troubleshoot complex issues.
· Strong communication and collaboration skills.

Good to have skills:-

•        Experience in Spark, Hadoop

•        Experience with MAVEN, Spring, XML, Tomcat

•        Experience in Unix and shell scripting and SQL server.

•        Experience with source code version control systems like GIT