Senior AI Engineer

Job Description

About the Role We are seeking a highly skilled and versatile Senior AI Engineer with over 5 years of hands-on experience to join our client’s team in Pune. This role focuses on designing, developing, and deploying cutting-edge AI and machine learning solutions for high-scale, high-concurrency applications where security, scalability, and performance are paramount. You will work closely with cross-functional teams, including data scientists, DevOps engineers, security specialists, and business stakeholders, to deliver robust AI solutions that drive measurable business impact in dynamic, large-scale environments. Key Responsibilities Architect, develop, and deploy advanced machine learning and deep learning models across domains like NLP, computer vision, predictive analytics, or reinforcement learning, ensuring scalability and performance under high-traffic conditions. Preprocess, clean, and analyze large-scale structured and unstructured datasets using advanced statistical, ML, and big data techniques. Collaborate with data engineering and DevOps teams to integrate AI/ML models into production-grade pipelines, ensuring seamless operation under high concurrency. Optimize models for latency, throughput, accuracy, and resource efficiency, leveraging distributed computing and parallel processing where necessary. Implement robust security measures, including data encryption, secure model deployment, and adherence to compliance standards (e.g., GDPR, CCPA). Partner with client-side technical teams to translate complex business requirements into scalable, secure AI-driven solutions. Stay at the forefront of AI/ML advancements, experimenting with emerging tools, frameworks, and techniques (e.g., generative AI, federated learning, or AutoML). Write clean, modular, and maintainable code, along with comprehensive documentation and reports for model explainability, reproducibility, and auditability. Proactively monitor and maintain deployed models, ensuring reliability and performance in production environments with millions of concurrent users. Required Qualifications Bachelor’s or master’s degree in computer science, Machine Learning, Data Science, or a related technical field. 3 to 5 years of experience building and deploying AI/ML models in production environments with high-scale traffic and concurrency. Advanced proficiency in Python and modern AI/ML frameworks, including TensorFlow, PyTorch, Scikit-learn, and JAX. Hands-on expertise in at least two of the following domains: NLP, computer vision, time-series forecasting, or generative AI. Deep understanding of the end-to-end ML lifecycle, including data preprocessing, feature engineering, hyperparameter tuning, model evaluation, and deployment. Proven experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services (e.g., SageMaker, Vertex AI, or Azure ML). Strong knowledge of containerization (Docker, Kubernetes) and RESTful API development for secure and scalable model deployment. Familiarity with secure coding practices, data privacy regulations, and techniques for safeguarding AI systems against adversarial attacks. Preferred Skills Expertise in MLOps frameworks and tools such as MLflow, Kubeflow, or SageMaker for streamlined model lifecycle management. Hands-on experience with large language models (LLMs) or generative AI frameworks (e.g., Hugging Face Transformers, LangChain, or Llama). Proficiency in big data technologies and orchestration tools (e.g., Apache Spark, Airflow, or Kafka) for handling massive datasets and real-time pipelines. Experience with distributed training techniques (e.g., Horovod, Ray, or TensorFlow Distributed) for large-scale model development. Knowledge of CI/CD pipelines and infrastructure-as-code tools (e.g., Terraform, Ansible) for scalable and automated deployments. Familiarity with security frameworks and tools for AI systems, such as model hardening, differential privacy, or encrypted computation. Proven ability to work in global, client-facing roles, with strong communication skills to bridge technical and business teams. Show more Show less