AIML Engineer

2 weeks ago

Bengaluru, India DataZymes Analytics Pvt. Ltd. Full time



AIML Engineer

Job Summary

We are looking for a skilled AI/ML Engineer with 3-4 years of experience in building and deploying scalable machine learning and Generative AI solutions. The ideal candidate should have a strong foundation in core AI/ML concepts, deep learning, NLP, and experience with Generative AI frameworks.

Who We Are Looking For

An enthusiastic self-starter who will work with minimal guidance, has strong Python programming skills, and hands-on experience deploying end-to-end AI/ML solutions. A first-principle understanding of databases, deep learning and LLMs is also required.

Required Skills and Qualifications

1.      3+ years of work experience in Python programming for AI/ML, deep learning, and Generative AI model development

2.      Proficiency in TensorFlow/PyTorch, Hugging Face Transformers and Langchain libraries

3.      Hands-on experience with NLP, LLM prompt design and fine-tuning, embedding, vector databases and genetic frameworks

4.      Strong understanding of ML algorithms, probability and optimization techniques

5.      6+ years of experience in deploying models with Docker, Kubernetes, and cloud services (AWS Bedrock, SageMaker, GCP Vertex AI) through APIs, and using MLOps and CI/CD pipelines

6.      Familiarity with retrieval-augmented generation (RAG), cache-augmented generation (CAG), retrieval-integrated generation (RIG), low-rank adaptation (LoRA) fine-tuning

7.      Ability to write scalable, production-ready ML code and optimized model inference

8.      Experience with developing ML pipelines for text classification, summarization and chat agents 

9.      Prior experience with SQL and noSQL databases, and Snowflake/Data bricks

What You Will Be Doing
As an AI/ML Engineer in the AI center of excellence (COE) at DataZymes, you will be developing and maintaining end-to-end AI solutions to business problems. Key responsibilities are listed below:


1.      Design, develop, and deploy AI/ML models for various applications, including NLP and structured data

2.      Implement, prompt, fine-tune, and optimize Generative AI models, such as LLMs and diffusion models

3.      Develop and maintain data pipelines, features engineering workflows, and model training infrastructure

4.      Work with large-scale datasets, ensuring data quality and pre-processing for training and inference

5.      Optimize model performance, reducing latency, and improving efficiency for real-time AI applications

6.      Deploy models using MLOps best practices on cloud platforms (AWS, GCP)

7.      Collaborate with cross-functional teams, including data engineers, software developers, and product managers to develop AI solutions to business problems

8.      Implement responsible AI practices, ensuring fairness, interpretable, and ethical AI adoption




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