AI/ML Engineer
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Company: Willware Technologies
Role: AI/ML Engineer
Location: Noida
Experience: 4 - 6 Years
We are looking for an experienced AI/ML Engineer with strong hands-on expertise in building, training, and deploying machine learning models and AI-driven solutions. The ideal candidate will have a solid background in Python, data engineering, ML frameworks, and cloud platforms.
Design, develop, and deploy Machine Learning and Deep Learning models.
Build data pipelines, data preprocessing workflows, and feature engineering processes.
Implement ML algorithms such as classification, regression, clustering, NLP, and recommendation systems.
Work with LLMs, Generative AI, and model fine-tuning when required.
Optimize model performance, evaluate metrics, and perform hyperparameter tuning.
Deploy ML models using Docker, CI/CD pipelines, and cloud services (AWS/Azure/GCP).
Collaborate with data engineers, product teams, and software developers to integrate models into production systems.
Research and experiment with new AI/ML technologies, tools, and frameworks.
Strong programming skills in Python (NumPy, Pandas, Scikit-learn).
Hands-on experience with TensorFlow, PyTorch, Keras, or similar frameworks.
Experience in NLP, computer vision, or generative AI projects.
Knowledge of ML Ops, model deployment, and cloud platforms (AWS/GCP/Azure).
Good understanding of statistics, probability, and data modelling.
Experience with SQL/NoSQL databases and data processing tools.
Ability to build end-to-end AI/ML solutions independently.
Job ID: 152219201
Skills:
Machine Learning, PostgreSQL, Deep Learning, Tensorflow, Pytorch, Gcp, Opencv, FastAPI, Rest Apis, Azure, Python, Computer Vision, AWS, embeddings, AWS Bedrock, LLMs, Hugging Face, Anthropic, prompt engineering, Vector Databases, RAG, OpenAI
Skills:
Tensorflow, Pytorch, Azure, Google Cloud, Deep Learning, AWS, Generative AI, Python Programming Language
Skills:
Prometheus, Grafana, Tensorflow, Cloudwatch, Pytorch, Docker, AWS ECS, AWS CodePipeline, Rest Apis, Python, Scikit-learn, vector databases, Pinecone, GRPC, async job processing, GitHub Actions, OpenTelemetry, FAISS, CI CD pipelines
Skills:
Apis, Docker, FastAPI, Python, Kubernetes, Multi-Agent Communication, enterprise engineering tools, cloud platforms, MCP Servers, Enterprise Connectors, Workflow Engine, VS Code integrations, Agent SDK, Shared Prompt Library
Skills:
spatial data , Computer Vision, MLops, XGBoost, Databricks, Python, time-series methods, data pipelines, classical ML fundamentals, ONNX, model evaluation, quantization
