Title: AI/ML Senior Engineer
Job Description:
We are looking for a highly skilled and experienced Sr. AI/ML Engineer with deep technical expertise in machine learning, deep learning, Generative AI and Agentic AI. The ideal candidate will have a strong programming foundation in Python and hands-on experience with modern ML/DL frameworks, version control systems, and data pipeline tools. This role requires both individual contribution and leadership in driving AI initiatives, while effectively communicating with cross-functional teams and stakeholders.
Key Responsibilities:
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Lead the design, development, and deployment of ML/DL models for real-world applications.
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Apply advanced techniques such as ensemble learning, transformers, GANs, LSTMs, and reinforcement learning.
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Work across diverse domains like NLP, computer vision, or recommendation systems based on project needs.
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Build scalable APIs and services using Flask, Django, or FastAPI.
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Collaborate with data engineering teams to ensure data readiness for model training and evaluation.
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Evaluate and fine-tune models using techniques like cross-validation, hyperparameter tuning, and performance metrics.
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Drive GenAI adoption by leveraging LLM APIs for inference and contribute to LLM training and deployment (if applicable).
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Document solution architecture, workflows, and technical implementation details clearly.
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Mentor junior engineers and collaborate with product managers, data scientists, and other technical teams.
Required Skills & Qualifications:
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5+ years of hands-on experience in AI/ML and deep learning.
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Strong programming skills in Python and good understanding of object-oriented programming.
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Deep knowledge of neural networks including GANs, transformers, LSTMs, etc.
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Proficient in scikit-learn, pandas, NumPy, and frameworks like TensorFlow-Keras or PyTorch.
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Experience with version control tools such as Git and GitHub.
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Solid skills in data visualization tools like Matplotlib, Seaborn, or similar.
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Familiarity with SQL and NoSQL databases.
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Experience building RESTful APIs using Django, Flask, or FastAPI.
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Hands-on experience with GenAI models, especially using LLM APIs for inference.
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Certifications in AI/ML or cloud-based AI platforms (AWS, GCP, Azure).
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Good understanding of model evaluation techniques and performance metrics.
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Outstanding verbal and written communication skills, with the ability to clearly articulate complex technical topics.
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Experience in MLOps tools like MLflow, Kubeflow, or Weights & Biases’
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Oil & Gas, refinery operations & financial services exposure is preferred
