Description :

Role : AI/ML Engineer

Experience : 8 - 13 Years (3 5 years specifically in AI/ML)

Location : Regional Tech Hub / Remote

Industry : Technology / Data Science / AI Research

Education : Bachelors, Masters, or PhD in Computer Science, Data Science, Statistics, or a related quantitative field.

Role Summary :

We are seeking a high-caliber AI/ML Engineer to lead the development of next-generation intelligent systems.

In this role, you will act as an "AI Solutions Architect," responsible for designing and deploying end-to-end machine learning models that solve complex business challenges.

You will bridge the gap between traditional predictive modeling and cutting-edge Generative AI, with a specific focus on Agentic AI workflows and forecasting optimization.

The ideal candidate is a technical powerhouse with deep expertise in Foundation Models and MLOps, capable of moving research-grade algorithms into scalable production environments across cloud platforms like AWS, Azure, or GCP.

Responsibilities :

- Advanced AI/ML Solutioning : Design and deliver end-to-end AI/ML solutions with a proven track record of solving high-impact business problems.

- Agentic AI & GenAI Development : Leverage Foundation Models to build and optimize Agentic AI workflows, creating autonomous systems capable of complex reasoning and task execution.

- Forecasting & Optimization : Apply advanced statistical modeling and machine learning algorithms to solve large-scale forecasting and optimization problems.

- Deep Learning Architecture : Develop and refine complex architectures using TensorFlow or PyTorch, specializing in NLP, Computer Vision, or Reinforcement Learning.

- Big Data Engineering : Utilize big data technologies such as Hadoop and Spark to process massive datasets for model training and evaluation.

- MLOps & Deployment : Implement robust MLOps practices to automate model deployment, monitoring, and retraining cycles, ensuring long-term model reliability.

- Cloud Infrastructure Management : Architect and deploy AI solutions on major cloud platforms (AWS, Azure, or GCP), ensuring scalability and cost-efficiency.

- Algorithm & Statistical Modeling : Maintain a deep understanding of core ML algorithms and deep learning frameworks to select the most efficient approach for diverse use cases.

- Cross-Functional Leadership : Partner with data scientists, engineers, and product leads to align AI initiatives with organizational strategy and technical objectives.

- Technical Communication : Translate complex AI/ML trade-offs and model performance metrics into clear insights for both technical and non-technical stakeholders.

Technical Requirements :

- Industry Experience : 8+ years of total software/data experience with 35 years focused specifically on AI/ML.

- Programming Mastery : Strong proficiency in Python, R, or Java.

- Framework Depth : Deep hands-on experience with TensorFlow or PyTorch.

- GenAI Stack : Proven experience with Foundation Models and building Agentic AI solutions.

- Data Scale : Practical experience with Spark or Hadoop for big data processing.

- Cloud & MLOps : Familiarity with cloud-native ML tools (e.g., SageMaker, Vertex AI) and CI/CD for ML.

Preferred Skills :

- Reinforcement Learning : Experience in building self-learning systems for dynamic environments.

- Advanced NLP : Expertise in fine-tuning Large Language Models (LLMs) and implementing RAG (Retrieval-Augmented Generation).

- Research Contribution : Published research or contributions to open-source AI/ML libraries