The company is looking to solve real-world applications using machine learning models and improve business workflows and processes.
Requirements
- Understands fundamental concepts, practices, and procedures of machine learning field.
- Data discovery, data aggregation, and feature engineering with SQL query writing skills.
- Training, evaluating, optimizing, deploying, and maintaining machine learning models on production systems.
- Strong development skills in Python programming language and have experience in developing data-driven, scalable, and reliable applications with Amazon Web Services (AWS).
- Utilization of popular open-source machine learning/deep learning libraries like LangChain, HuggingFace, Tensorflow, scikit-learn, pandas, pyTorch, and Keras.
- Experience working with relational, non-relational, and high-scale data processing and storage frameworks like Structured Query Language (SQL), AWS RedShift, Aurora, S3, DynamoDB, MySQL, PostgreSQL.
- Experience with AWS Serverless architecture and AWS native services like BedRock, EC2, Lambda, Step Functions, SageMaker, Rekognition, Comprehend, Lex/Polly, and Transcribe.
Responsibilities
- Designs, develops, and deploys machine learning models for real-world applications.
- Builds scalable pipelines for data ingestion, pre-processing, training, and inference.
- Owns end to end development of machine learning algorithms including data analysis, feature engineering, model development, training, validation, and performance evaluation.
- Designs, implements, and optimizes retrieval-augmented generation (RAG) pipelines that combine large language models (LLMs) with vector search/retrieval systems.
- Builds data ingestion and embedding pipelines for efficient indexing and retrieval.
- Fine-tunes and adapts LLMs for domain-specific tasks such as instruction tuning, prompt engineering, low-rank adaptation (LoRA), etc.
- Engages in both engineering and research, exploring latest ML algorithms, solution architectures, and cutting-edge approaches to improve retrieval and generation performance.
Other
- Master’s degree in Machine Learning, Deep Learning, or a computer science-related field. PhD preferred.
- Minimum three (3) years of relevant work experience in the areas below, or any equivalent education and/or experience from which comparable knowledge, skills and abilities have been demonstrated/achieved:
- Works with stakeholders to translate business requirements into robust technical solutions that deliver measurable impact.
- Works with engineering teams to continuously scale and advance machine learning across the organization.
- Performs other related duties and projects as business needs require at direction of management.
