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Oversee the entire lifecycle of AI/ML features, ensuring their successful implementation, scalability, and maintenance
Train, evaluate, and fine-tune AI/ML models using the most suitable techniques, architectures, and frameworks
Implement key machine learning strategies across the business and collaborate with stakeholders for effective delivery
Coordinate end-to-end delivery of AI-driven projects, working closely with cross-functional teams including data engineering, product, and DevOps
Stay up-to-date with the latest AI/ML and Generative AI research, frameworks, and tools to contribute to continuous innovation
Develop and maintain comprehensive documentation for AI and data science solutions
Develop and maintain APIs and microservices for integrating AI models with other business systems and products
Perform model testing, monitoring, and troubleshooting to ensure accuracy, reliability, and efficiency in production environments
Design, build, and deploy Generative AI components (e.g., large language models, text/image generation, summarization tools) to enhance product capabilities
Leverage frameworks such as LangChain, Hugging Face, and OpenAI APIs to integrate LLM-based features into existing workflows and systems
Experiment with retrieval-augmented generation (RAG), embeddings, and prompt engineering techniques to improve model outputs
Collaborate with cloud and DevOps teams to implement MLOps pipelines for continuous integration, delivery, and monitoring of AI models
Provide technical support and knowledge transfer to clients and internal teams, ensuring smooth adoption of AI technologies
Contribute to AI governance and ethical considerations for responsible AI usage
Mentor junior engineers and foster a culture of experimentation and learning in advanced AI areas, including Generative AI
Requirements:
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field
5+ years of experience in designing, developing, and deploying AI/ML solutions
Strong understanding of AI/ML algorithms, deep learning architectures, and frameworks such as TensorFlow, PyTorch, OpenCV, and Scikit-learn
Proficient in Python and experienced with frameworks like LangChain, TensorFlow, PyTorch, and Hugging Face
Experience with cloud platforms such as AWS, GCP, and Azure, and familiarity with managed AI/ML services (e.g., SageMaker, Vertex AI)
Expertise in Natural Language Processing (NLP), Computer Vision, and model deployment workflows
Hands-on experience developing and deploying Generative AI applications, including LLMs, diffusion models, and transformer-based architectures
Familiar with vector databases (e.g., FAISS, Pinecone, Chroma) and embedding-based retrieval systems
Experience with MLOps practices, including CI/CD, model versioning, monitoring, and scaling
Knowledge of Big Data platforms such as Apache Kafka, Hadoop, and Snowflake, and experience using PySpark and Databricks for data engineering tasks
Strong software engineering background with a focus on clean, efficient, and maintainable code
Excellent analytical, problem-solving, and communication skills
Ability to work independently, communicate effectively with clients, and mentor junior team members
Ability to thrive in a fast-paced, dynamic, and innovation-driven environment
Passionate about leveraging AI and Generative AI technologies to drive real-world business growth and innovation
Nice to have:
Familiarity with Generative AI frameworks and APIs such as OpenAI, Anthropic, or Stability AI is an advantage
Experience with distributed systems and model optimization is a plus