Sr. AI/ML Engineer

ESP Engineered

Hyderabad

On-site

INR 1,500,000 - 2,500,000

Full time

14 days+

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Job summary

ESP Engineered in Hyderabad, India, is seeking a highly skilled Sr. AI/ML Engineer with expertise in machine learning and deep learning. The candidate will lead AI initiatives, manage ML/DL model development, and mentor junior engineers. Key skills include Python programming, experience with frameworks such as TensorFlow and PyTorch, and familiarity with MLOps tools. The company values effective communication and collaboration across teams. Interest in Oil & Gas, refinery operations, and financial services is preferred.

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, and LSTMs.

Responsibilities

  • Lead the design, development, and deployment of ML/DL models for real-world applications.
  • Evaluate and fine-tune models using techniques like cross-validation and hyperparameter tuning.
  • Mentor junior engineers and collaborate with product managers and data scientists.

Skills

Machine learning
Deep learning
Python
Generative AI
Neural networks
API development
Data visualization
MLOps

Education

Certifications in AI/ML or cloud-based AI platforms (AWS, GCP, Azure)

Tools

TensorFlow-Keras
PyTorch
scikit-learn
Git
GitHub
MATLAB
MLflow
Kubeflow
Weights & Biases

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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