AI/ML Engineer

5 hours ago

bangalore, India TransPerfect Full time

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 RoleWe’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 ResponsibilitiesArchitect 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 & QualificationsBachelor’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 QualificationsExperience 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.

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