AI Engineers

Key Responsibilities:

Design, develop, and deploy machine learning and AI models
Build and maintain data pipelines for training and inference
Work on supervised and unsupervised learning algorithms
Implement NLP, Computer Vision, or Deep Learning solutions
Optimize models for performance, scalability, and accuracy
Collaborate with data engineers, analysts, and product teams
Deploy models using cloud platforms (AWS/Azure/GCP)
Monitor model performance and perform continuous improvements
Conduct data preprocessing, feature engineering, and model evaluation
Document models, processes, and experiments

Required Skills & Qualifications:

Technical Skills:

Strong proficiency in Python:

Experience with Machine Learning libraries:

Scikit-learn
Tensor Flow / Py Torch

Knowledge of data manipulation tools (Pandas, Num Py)
Experience with ML algorithms (regression, classification, clustering)

Familiarity with Deep Learning frameworks:

Knowledge of NLP or Computer Vision techniques:

Experience in model deployment (APIs, microservices)
Strong understanding of statistics and probability

• Primary skills:Domain->Turbomachinery->Steam Turbine->Rotor

Preferred Skills (Nice-to-Have)

Experience with Generative AI / LLMs (GPT, Lang Chain, Hugging Face)
Knowledge of MLOps tools (MLflow, Kubeflow, Airflow)

Experience with Docker and Kubernetes:

Familiarity with Big Data tools (Spark, Py Spark)
Experience with REST APIs and microservices architecture
Knowledge of cloud AI services (AWS Sage Maker, Azure ML, GCP AI)
Understanding of vector databases and embeddings (FAISS, Pinecone)
Exposure to CI/CD pipelines and DevOps practices

Education: MCA,MSc,MTech,Bachelor of Engineering,BCA,BSc,BTech

Preferred skills: Technology->AI-AI Engineering->AI/ML Solution Architecture and Design