Sr Machine Learning Engineer
Location: India - Bangalore
Experience: 5 - 8 Years
Must Haves -
Minimum Relevant Experience: 4-5 Years AI/ML
1. ML: Algorithms
2. Model Ops: Deployment Monitoring Versioning
3. Data Engineering: ETL FastAPI Pipeline Development
4. Tooling Proficiency: Docker Kubernetes MLflow
5. Frameworks: Scikit-learn TensorFlow PyTorch
Experience Level: 5 years
Fundamental knowledge of supervise and unsupervised learning and their
applications inreal world business scenarios.
Familiarity with End-2-End Machine Learning model development life cycle.
Experience in creating data processing pipelines and API development (Fast API).
Experience with deploying and maintaining ML/DL models in production
model monitoring and knowledge of concept/data drift model
reproducibility code model and data versioning.
Experience with SQL and NoSQL MLflow GitHub docker Kubernetes ELK or similar stack.
Hands on with text and image processing: cleaning transformations and data preparationfor modelling. And should be comfortable with libraries like Pandas NumPy OpenCV PIL Spacy transformers etc.
Should have working knowledge of machine learning frameworks like Scikitlearn PyTorch/ Tensorflow/Keras.
Experience with cloud computing platforms like GCP and AWS.
Should understand LLMs Open AI API model fine-tuning and prompt engineering.
Exposure to CI/CD principles and associated tools.
Good to have:
Experience with deep learning frameworks
Strong experience in programming and statistics
Excellent verbal and written communication skills
Highly developed attention to detail
Strong presentation skills
Ability to work well in a team environment
Excellent problem-solving skill
prompt engineering,llms,machine learning,pipeline development,model ops,github,pytorch,open ai api,scikit-learn,transformers,kubernetes,gcp,data engineering,opencv,aws,mlflow,pandas,ops,algorithms,pil,spacy,nosql,sql,fastapi,ml,elk,numpy,etl,artificial intelligence,docker,tensorflow,model fine-tuning