AI/ML Engineer

Overview

On Site
$95 - $100
Contract - W2
Contract - 1 month(s)
No Travel Required

Skills

Python
NLP
GenerativeAI
LLMs
MachineLearning

Job Details

Job Description:

Pay Range: $95hr - $100hr

Responsibilities:
  • XXgn, develop, and deploy intent classification and intent detection models using LLMs and traditional NLP methods.
  • Build and optimize Natural Language Generation (NLG) pipelines for chatbot responses, summarization, content creation, or knowledge grounding.
  • Architect and implement LangChain and LangGraph based applications for LLM-driven workflows (e.g., autonomous agents, RAG systems).
  • Develop scalable machine learning pipelines using the AWS tech stack (e.g., Sagemaker, LamClienta, Bedrock, Step Functions, DynamoDB, Athena).
  • Integrate and fine-tune foundation models via AWS Bedrock, including Amazon Titan, Anthropic Claude, or Meta Llama.
  • Collaborate closely with product managers, ML researchers, and backend engineers to translate business requirements into robust AI solutions.
  • Lead experimentation efforts, conduct A/B testing, and ensure continuous evaluation of deployed ML models.
  • Candidatetor junior ML engineers and contribute to best practices in MLOps, model governance, and responsible AI.
Required Qualifications:
  • Total 10+ in IT with 4 to 5 + years of experience in machine learning, with a focus on NLP and Generative AI.
  • Strong experience building and deploying intent detection, text classification, sequence tagging, and entity recognition models.
  • Proficient in LangChain, LangGraph, vector databases (e.g., FAISS, Pinecone), and orchestration of LLM workflows.
  • Deep knowledge of AWS Bedrock, Amazon SageMaker, Lambda, DynamoDB, Step Functions, etc.
  • Experience working with open-source LLMs (LLaMA, Mistral, Falcon) or commercial APIs (Claude, GPT-4, etc.).
  • Proficient in Python, with a solid grasp of ML frameworks such as PyTorch, HuggingFace Transformers, scikit-learn.
  • Strong understanding of MLOps practices including model versioning, CI/CD for ML, monitoring, and auto-scaling.
  • Bachelor s or Master s in Computer Science, Data Science, or a related field.
Nice to Have:
  • Experience integrating RAG (Retrieval-Augmented Generation) systems at scale.
  • Familiarity with vector search using Amazon OpenSearch, Pinecone, or Weaviate.
  • Experience with streaming data processing (e.g., AWS Kinesis, Kafka).
  • Contributions to open-source AI/ML or NLP projects.
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