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AI / ML Engineer
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- Posted 4 days ago
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Job Description
THE WORK: Explore new horizons with enthusiasm and curiosity. You will perform independently and become a subject matter expert while actively participating and contributing in team discussions. Your contributions will help provide thoughtful solutions to work-related challenges. This opportunity invites you to engage deeply with advanced Machine Learning, fostering growth and innovation. Join us in shaping the future with your expertise and passion.
Responsibilities: Design and develop AI/ML and Generative AI solutions using Python
Build and deploy applications leveraging Large Language Models (LLMs)
Develop end-to-end pipelines including data ingestion, preprocessing, model integration, and deployment
Implement prompt engineering and fine-tuning strategies for LLMs
Integrate AI services into web/mobile/backend applications via APIs
Work with vector databases and embeddings for semantic search and RAG architectures
Optimize models and pipelines for performance, latency, and cost
Collaborate with cross-functional teams to translate business requirements into AI solutions
Ensure responsible AI practices including data privacy, bias mitigation, and explainability
Monitor and improve model performance in production environments
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Required Skills & Qualifications
6-8 years of experience in software engineering / AI / ML, Python roles,
Strong programming expertise in Python
Hands-on experience with ML/DL frameworks like PyTorch or TensorFlow
Experience with LLM frameworks such as LangChain or LlamaIndex
Solid understanding of NLP concepts and transformer-based models
Experience with REST APIs and microservices architecture
Familiarity with vector databases (e.g., Pinecone, FAISS, Weaviate)
Experience with version control systems like Git
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Preferred Qualifications
Experience working with APIs from providers like OpenAI or open-source LLMs (Llama, Mistral)
Knowledge of Retrieval-Augmented Generation (RAG) architectures
Experience with model fine-tuning and evaluation techniques
Exposure to cloud platforms (AWS / GCP) for deployment (excluding Azure)
Understanding of containerization tools like Docker
________________________________________
Soft Skills
Strong analytical and problem-solving skills
Ability to translate complex AI concepts into practical solutions
Good communication and stakeholder management skills
Ability to work independently and in collaborative environments
________________________________________
Nice to Have
Experience with AI agents / autonomous workflows
Knowledge of MLOps practices and CI/CD for ML pipelines
Exposure to multimodal AI (text, image, audio models)
Experience with real-time AI applications (chatbots, voice bots, copilots)
Responsibilities: Design and develop AI/ML and Generative AI solutions using Python
Build and deploy applications leveraging Large Language Models (LLMs)
Develop end-to-end pipelines including data ingestion, preprocessing, model integration, and deployment
Implement prompt engineering and fine-tuning strategies for LLMs
Integrate AI services into web/mobile/backend applications via APIs
Work with vector databases and embeddings for semantic search and RAG architectures
Optimize models and pipelines for performance, latency, and cost
Collaborate with cross-functional teams to translate business requirements into AI solutions
Ensure responsible AI practices including data privacy, bias mitigation, and explainability
Monitor and improve model performance in production environments
________________________________________
Required Skills & Qualifications
6-8 years of experience in software engineering / AI / ML, Python roles,
Strong programming expertise in Python
Hands-on experience with ML/DL frameworks like PyTorch or TensorFlow
Experience with LLM frameworks such as LangChain or LlamaIndex
Solid understanding of NLP concepts and transformer-based models
Experience with REST APIs and microservices architecture
Familiarity with vector databases (e.g., Pinecone, FAISS, Weaviate)
Experience with version control systems like Git
________________________________________
Preferred Qualifications
Experience working with APIs from providers like OpenAI or open-source LLMs (Llama, Mistral)
Knowledge of Retrieval-Augmented Generation (RAG) architectures
Experience with model fine-tuning and evaluation techniques
Exposure to cloud platforms (AWS / GCP) for deployment (excluding Azure)
Understanding of containerization tools like Docker
________________________________________
Soft Skills
Strong analytical and problem-solving skills
Ability to translate complex AI concepts into practical solutions
Good communication and stakeholder management skills
Ability to work independently and in collaborative environments
________________________________________
Nice to Have
Experience with AI agents / autonomous workflows
Knowledge of MLOps practices and CI/CD for ML pipelines
Exposure to multimodal AI (text, image, audio models)
Experience with real-time AI applications (chatbots, voice bots, copilots)
More Info
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Key Skills
About Company
Skills:
Cursor, Code, Tensorflow, Numpy, Git, Pandas, Pytorch, Terraform, Docker, Azure, Python, Kubernetes, Azure DevOps, scikit-learn, AKS, Claude, CI CD, GitHub Actions, RAG, Bicep
Skills:
Databases, Apis, Logging, Cloud deployment, Automated Testing, Git, Enterprise Security, Containers, Python, retrieval tool calling workflow orchestration, identity secrets management, CI CD, alerting, Incident Investigation, event-driven integrations, access controls, human-in-the-loop processes, performance optimization, Production Monitoring
Skills:
Sql, FastAPI, Python, LangChain, NL-to-SQL, AWS Bedrock, Pinecone, LangGraph, FAISS, RAG solutions, Pydantic, ChromaDB, AWS AgentCore
Skills:
Distributed Systems, LangChain, policy enforcement, LLMs, agent orchestration frameworks, LangGraph, ML platforms, cost controls, model adapters, embeddings pipelines, stateful workflow design, vector DBs, external APIs, RAG retrieval, observability
Skills:
Machine Learning, MLops, Docker, Rest Apis, Kubernetes, LangChain, GenAI LLMs, LLM integration, Pinecone, Azure OpenAI, prompt engineering, Vector Databases, Chroma, Hugging Face models, FAISS, RAG, cloud-based AI ML solutions, OpenAI, Weaviate, LlamaIndex