AI ML Engineer

We’re looking for a highly skilled

AI/ML Engineer

to design, develop, and deploy advanced machine learning solutions that solve complex business challenges. You’ll work closely with cross-functional teams—Data Engineers, Product Managers, and Software Developers—to bring AI-powered features and insights into production-ready systems.

Key Responsibilities

• Design \& Develop ML Models:

Build, train, and optimize machine learning and deep learning models for real-world applications (e.g., NLP, computer vision, recommendation systems).

• Data Preparation \& Feature Engineering:

Collect, clean, and preprocess large-scale datasets for model development.

• Deployment \& Integration:

Package models into APIs or services, deploy to cloud platforms (AWS, Azure, GCP), and ensure scalability and reliability.

• Monitor \& Maintain Models:

Track model performance in production, retrain as needed, and manage version control.

• Collaboration:

Partner with product and engineering teams to translate business requirements into technical solutions.

• Innovation:

Research and implement cutting-edge ML algorithms and tools to improve existing processes and products.

• Transformers, Agentic AI, RAG, Advance RAG, Deep learning basics, Python

Required Skills \& Experience

• 7\+ years of experience in AI/ML development and deployment.
• Proficiency in

Python

(pandas, NumPy, scikit-learn) and at least one deep learning framework (

TensorFlow

or

PyTorch

).

• Strong understanding of algorithms, statistics, and machine learning techniques (e.g., regression, classification, clustering, CNNs, RNNs).
• Experience with

cloud platforms

(AWS SageMaker, Azure ML, or GCP AI Platform).

• Familiarity with

data engineering concepts

(ETL, data pipelines, SQL/NoSQL databases).

• Hands-on experience deploying ML models in production environments (e.g., REST APIs, Docker, Kubernetes).
• Solid problem-solving skills and the ability to work in an agile, fast-paced environment.

Preferred Qualifications

• Exposure to

MLOps

practices (CI/CD for ML, model monitoring, automated retraining).

• Experience with

natural language processing (NLP)

or

computer vision

projects.

• Knowledge of big data tools like

Spark

or

Hadoop

.

• Master’s degree in Computer Science, Data Science, or a related field.

Thanks,

Renuka