Machine Learning Engineer
- Posted 2 months ago
- Be among the first 10 applicants
Job Description
- Looking for a Gen AI candidate with Generative AI (LLMs, Transformers) LangChain, LlamaIndex, MLOps (MLflow, Kuberflow),Prompt engineering.
- Knowledge of APIs (OpenAI, Cohere, etc.)
- Hands on custom model building and training Agentic AI architecture driven application building.
- Different orchestration tools exposure like , crewai, airflow, prefect.
- Any MCP server building exposure and cloud agnostic model evaluation.
NOTE: Looking for a senior role with 6+years of experience, who is open to work from Bangalore.
More Info
Key Skills
LangChain
Generative AI
Prompt engineering
orchestration tools
LLMs
custom model building
Agentic AI architecture
MLflow
MCP server building
crewai
cloud agnostic model evaluation
prefect
OpenAI
Kuberflow
Cohere
LlamaIndex
About Company
Skills:
error analysis , Tensorflow, Pytorch, Docker, Python, LangChain, Evaluation metrics, pgvector, Qdrant, Statistical testing, Container orchestration, MLflow, Pinecone, LLM orchestration frameworks, API integrations, Cloud deployments, Vector search engineering, LlamaIndex, MLOps fundamentals
Skills:
Sql, Tensorflow, Pytorch, Gcp, MLops, Docker, Spark, Azure, Kubernetes, Python, AWS, Generative AI, LLMs, Scikit-learn, Agentic AI, RAG
Skills:
Svm, XGBoost, Python, Decision Trees, Clustering, MLops, Restful Apis, Agent reasoning patterns, Prompt engineering, Feature selection, scikit-learn, RAG systems, Data preprocessing, Conversation analytics, AI system observability frameworks, LLM conversational AI systems, Feature engineering, semantic search, AWS Sagemaker, LangChain, CrewAI, Vector databases, LightGBM, Ensemble models, Regression, Statistical Modeling, Agent frameworks, Context optimization
Skills:
Java, Docker, Kubernetes, Python, TFX, AWS SageMaker, Kubeflow, Google Vertex AI, Go, MLflow, Metaflow
Skills:
Machine Learning, Deep Learning, Tensorflow, Pytorch, Opencv, Python, Computer Vision, GenAI, Prompting, LLMs, GenAI systems, OCR engines, PIL, Fine-tuning