AI/ML Engineer Specialist

Role summary:
We are seeking a hands-on Specialist AI/ML Engineer to design, build and deploy intelligent systems that solve real-world product and business problems. This role requires strong expertise in model development, experimentation, and performance optimization, along with the ability to translate data into scalable AI Solutions.
You will work across the full AI lifecycle - from data preparation and model development to evaluation, deployment collaboration, and continuous improvement. The ideal candidate brings strong engineering discipline, experience operationalizing models, and the ability to work closely with cross-functional teams in a fast-paced environment.
This is an individual contributor role focused on building high-quality AI systems that are accurate, reliable, and production-ready.
Key Responsibilities
Model Development & Experimentation

• Design, develop, and optimize machine learning models for business use cases such as prediction, classification, forecasting, anomaly detection, and NLP tasks
  
• Conduct structured experimentation, hyperparameter tuning and performance benchmarking
  
• Transform structured and unstructured data into modeling-ready datasets
  
• Implement training and fine-tuning workflows using modern AI frameworks
  
• Define and track appropriate evaluation metrics to ensure robustness and generalization
  

AI System & Applied Intelligence

• Contribute to AI-Powered capabilities such as search, summarization, and intelligent assistance
  
• Support use cases involving LLMs, embeddings, and retrieval-based architectures when required
  
• Evaluate and compare different modeling approaches to improve accuracy and efficiency
  
  
• Improve system performance in terms of reliability, latency and cost
  

Deployment & Operational Readiness

• Collaborate with engineering teams to deploy models into production environments
  
• Contribute to versioning, validation, and monitoring strategies for AI systems
  
• Participate in debugging, root cause analysis, and performance improvements
  
• Maintain clean, reproducible training pipelines and documentation
  

Collaboration & Engineering Excellence

• Work closely with product managers, data engineers, and backend teams in an Agile environment
  
• Maintain clean code, well-documented experiments and structured project plans
  
• Contribute to shared AI best practices and reusable components
  
• Clearly communicate technical findings to both engineering and business stakeholders
  

Requirements
Required Skills & Experience

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Get Hired

• Strong experience in machine learning model development and evaluation
  
• Hands-on experience with TensorFlow / PyTorch
  
• Solid Python programming skills (Pandas, NumPy, Scikit-learn, SciPy, etc.,)
  
• Experience working with structured and unstructured datasets
  
• Understanding of NLP concepts and transformer-based architectures
  
• Experience building production-quality software in Collaborative environments
  
• Ability to run iterative development cycles and deliver measurable outcomes
  

Nice to Have

• Exposure to LLMs, embeddings, and RAG-based systems
  
• Familiarity with MLOps concepts (model versioning, CI/CD, monitoring)
  
• Experience deploying AI services on AWS
  
• Experience with experiment tracking tools (MLflow or similar)
  
• Experience working with SQL and relational databases