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