Job Summary
We are looking for a Machine Learning Engineer to design, build, and deploy ML models and algorithms that solve complex business problems. The ideal candidate will collaborate with data scientists, software engineers, and product teams to create scalable, efficient, and high-performing ML solutions for clients and internal platforms.
Key Responsibilities
Model Development & Implementation
- Design, implement, and maintain machine learning models for predictive analytics, NLP, computer vision, or recommendation systems
- Perform data preprocessing, feature engineering, and model selection
- Optimize models for accuracy, efficiency, and scalability
Data Handling & Analysis
- Collect, clean, and process structured and unstructured data
- Explore datasets to extract actionable insights and inform model development
- Ensure data quality, consistency, and compliance
Deployment & Integration
- Deploy ML models into production environments or SaaS platforms
- Collaborate with software engineers and DevOps teams for seamless integration
- Monitor, evaluate, and update models post-deployment
Research & Innovation
- Stay current with latest ML research, frameworks, and technologies
- Evaluate and experiment with new algorithms and tools
- Contribute to innovation in AI/ML solutions for enterprise and GCC clients
Collaboration & Documentation
- Work with cross-functional teams including product, analytics, and business stakeholders
- Document ML models, pipelines, and processes for reproducibility and reference
- Present findings and technical solutions in a clear and actionable manner
Required Skills & Qualifications
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field
- 37 years of experience in machine learning model development and deployment
- Strong programming skills in Python, R, or Java
- Hands-on experience with ML libraries/frameworks: TensorFlow, PyTorch, Scikit-learn, Keras
- Familiarity with NLP, computer vision, recommendation systems, or deep learning
- Knowledge of cloud platforms (AWS, GCP, Azure) for ML deployment
- Strong problem-solving, analytical, and communication skills
Preferred Qualifications
- Experience in MLOps, ML pipelines, and model versioning
- Exposure to big data tools: Spark, Hadoop, Kafka
- Previous work on SaaS products, enterprise IT solutions, or GCC projects
