AI/ML Engineer

AI/ML Engineer (Remote – Bangalore, India)
Location: Bangalore, India (Remote)
Contract: 5 months (with potential 12-month extension based on performance)
Client: A leading multinational telecommunications company (name disclosed at interview)
About the Role
We’re looking for an experienced AI/ML Engineer to join our advanced analytics and product innovation team.

In this role, you’ll design, develop, and deploy large-scale machine learning systems for speech, vision, and predictive analytics.

You’ll collaborate with cross-functional teams across data science, cloud engineering, and product management to drive AI adoption in next-generation telecommunications solutions.
Key Responsibilities
Architect and deploy large-scale ML models for speech, vision, and predictive analytics.
Lead research into emerging AI frameworks and tools.
Mentor junior and mid-level engineers, guiding best practices.
Collaborate with product managers and system engineers to integrate ML solutions into products.
Optimize models for scalability, accuracy, and efficiency.
Required Skills & Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical Engineering, or a related discipline.
3–6 years of experience in machine learning model design, training, and deployment.
Strong programming skills in Python (R a plus).
Proficiency in ML/DL frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras.
Experience with data processing frameworks such as Spark or PySpark.
Strong knowledge of SQL and working with relational databases.
Hands-on experience with Docker, Kubernetes, and CI/CD pipelines for model deployment.
Familiarity with cloud platforms (AWS, Azure, or GCP) and cloud-native ML tools.
Understanding of API development and integration for deploying AI services.
Excellent analytical, problem-solving, and collaboration skills.
Preferred Qualifications
Experience with Generative AI or LLM-based systems.
Knowledge of big data tools and distributed computing environments.
Familiarity with observability, model monitoring, and performance tuning.
Exposure to telecommunications or large-scale enterprise AI systems.