​My client, a prominent and acclaimed organization in the life science field, is presently seeking an adept Senior AI Engineer to join their team. In this role, you'll be an integral part of a dynamic team, contributing significantly to the design, implementation, and testing of state-of-the-art Machine Learning frameworks. You'll engage in rapid iterative prototyping, collaborating closely with experts in computer vision, machine learning, platform engineering, and research.

Responsibilities:

· Design, develop, and deploy tailored AI models for specific project needs, encompassing techniques such as NLP, Computer Vision, Speech & Conversational AI.

· Demonstrate a proficient understanding of Document AI development processes, models, and applications.

· Possess a solid grasp of LLMs with hands-on experience in Generative AI Models & their applications being a plus.

· Deliver and maintain end-to-end Machine Learning solutions in production, from data preparation to model update, utilizing MLOps methodologies.

· Collaborate with data scientists, ML engineers, and stakeholders to transition prototypes into production.

· Optimize algorithms to enhance performance and functionality.

· Integrate AI solutions into cloud platforms like AWS, Azure, or GCP.

· Stay abreast of the latest AI, LLMs, MLOps, and machine learning trends and best practices.

· Ensure the robustness, scalability, and reliability of AI solutions.

· Implement CI/CD pipelines using Azure DevOps/TFS.

· Provide technical leadership and mentorship in AI to team members.

· Work closely with cross-functional teams to integrate AI solutions into products and services.

Requirements:

· Minimum of 6+ years of experience in AI & ML.

· Expertise in biology, chemistry, engineering, data science, or machine learning.

· Proven experience in AI, ML, MLOps, Text Analytics, and Generative AI.

· Proficiency in programming languages like Python.

· Experience with machine learning frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn.

· Hands-on experience with cloud platforms such as AWS, Azure, or GCP.

· Familiarity with Machine Learning and Neural Network architectures like Ensemble Models, SVM, CNN, RNN, Transformers, etc.

· Proficiency in Natural Language Processing (NLP) tools like NLTK, Spacy, and Gensim.

· Familiarity with MLOps tools such as Kubeflow, MLflow, or Azure ML.

· Experience with SQL and NoSQL databases like MongoDB, Postgres, Neo4j, etc.

· Proficiency in RestAPI python frameworks such as Fast API/Flask/Django.

· Excellent problem-solving skills and a collaborative mindset.

· Strong communication skills to collaborate effectively with diverse teams.

· Ideally a Master's or PhD in Statistics, Mathematics, Computer Science, or another quantitative field.

· Knowledge and experience in statistical and data mining techniques such as GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.

· Experience in creating and utilizing advanced machine learning algorithms and statistics, including regression, simulation, scenario analysis, modelling, clustering, decision trees, neural networks, etc.

· Experience in querying databases and using statistical computer languages like R, Python, etc.

· Published research or contributions to open-source AI/ML projects.