Software Engineer - Machine Learning/LLM (5-8 yrs)

About the job

Java ML Engineer

Location : Bangaluru, IN

Duration : 6-12 Months

Role Overview :

We are seeking a skilled and innovative Software Engineer with expertise in Large Language Models (LLMs) to join our team.

The ideal candidate has hands-on experience using LLMs as a service from Java applications, alongside a deep understanding of the machine learning lifecycle.

This role involves building scalable AI solutions, collaborating with cross-functional teams, and contributing to cutting-edge AI initiatives.

Key Responsibilities :

- Connect, fine-tune, and optimize LLMs like OpenAI's GPT-4o, Anthropic's Claude, Google's Gemini

- Deploy models across different vendors, for example Azure OpenAI, Google Vertex or Amazon Bedrock

- Review and optimize architecture and design for existing and new LLM solutions

- Utilizing LLMs to optimize new or existing features in the product

- Train and deploy custom models for specific use cases

- Work closely with software engineering teams to integrate ML solutions into production environments.

- Run and make simple modifications in Java code, for example optimize a prompt or add a new vendor like Amazon Bedrock

- Experiment with new architectures, frameworks, and approaches to improve model performance and accuracy

- Collaborate with cross-functional teams, including data scientists, engineers, and product managers, to align ML solutions with business goals

Required Qualifications :

Experience :

- At least 3 years of professional experience in machine learning or AI development.

- Proven experience with LLMs and generative AI technologies.

Technical Skills :

- Basic knowledge of Java

- Hands-on experience with APIs and tools like OpenAI, Anthropic's Claude, Google Gemini, or AWS Bedrock.

- Familiarity with ML frameworks such as TensorFlow or Hugging Face.

- Strong understanding of data structures, algorithms, and distributed systems.

Cloud Expertise :

- Experience with AWS, GCP, or Azure, including services relevant to ML workloads

Data Engineering :

- Proficiency in handling large-scale datasets and implementing data pipelines.

- Experience with ETL tools and platforms for efficient data preprocessing.

Problem Solving :

- Strong analytical and problem-solving skills, with the ability to debug and resolve issues quickly