SR. AI Engineer

To be responsible for managing technology in complex projects ,providing technical guidance and ensuring successful delivery of solutions. (1.) To be responsible for providing technical guidance to a team of developers, enhancing their technical capabilities and increasing productivity. (2.) To conduct comprehensive code reviews, establish and oversee quality assurance processes, performance optimization , implementation of best practices and coding standards to ensure successful delivery of complex projects. (3.) To ensure process compliance in the assigned module| and participate in technical discussions / review as a technical consultant for feasibility study (technical alternatives, best packages, supporting architecture best practices, technical risks, breakdown into components, estimations). (4.) To collaborate with stakeholders to define project scope, objectives, deliverables and accordingly prepare and submit status reports for minimizing exposure & closure of escalations.

Additional requirement :

SR. AI Engineer

Skills-

Advanced AI Skills

Proficiency in Python

JD- "- Educational Qualifications : Graduate or Doctorate degree in information technology, Neuroscience, Business Informatics, Biomedical Engineering, Computer Science, Artificial Intelligence, or a related field. Specialization in Natural Language Processing is preferred.

• Experience Requirements : 8-10 years of experience in developing Data Science, AI, and ML solutions, with a specific focus on generative AI and LLMs in the MedTechHealthcareLife Sciences domain.
• Prior experience in identifying new opportunities to optimize the business through analytics, AIML and use case prioritization.
• The individual should be a thought leader having a well-balanced analytical business acumen, domain, and technical expertise.
• Large Language Model Expertise : Experience in working with and fine-tuning Large Language Models (LLMs), including the design, optimization of NLP systems, frameworks, and tools.
• Application Development with LLMs : Experience in building scalable applications using LLMs, utilizing frameworks such as LangChain, LlamaIndex, etc and productionizing machine learning and AI models.
• Language Model Development : Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications.
• Cloud Computing Expertise : Proven architect kind of experience in cloud computing, particularly with Azure Cloud Services.
• Technical Proficiency : Strong skills in UNIXLinux environments and command-line tools.
• Programming and ML Skills : Proficiency in Python, with a deep understanding of machine learning algorithms, deep learning, and generative models.
• Advanced AI Skills and Testing : Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch), hands-on experience in deploying AIML solutions as a serviceREST API on Cloud or Kubernetes, and proficiency in testing of developed AI components.
• Responsibilities also include data analysis preprocessing for training and fine-tuning language models. "