Applied AIML Lead- Python & Data Science Engineering

As an Applied AIML Engineer, you provide expertise and engineering excellence as an integral part of an agile team to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Leverage your advanced technical capabilities and collaborate with colleagues across the organization to drive best-in-class outcomes across various technologies to support one or more of the firm's portfolios., * Co-Develop and implement LLM-based, machine learning models and algorithms to solve complex operational challenges.

• Design and deploy generative AI applications to automate and optimize business processes.
• Collaborate with stakeholders & Data Scientists to understand business needs and translate them into technical solutions.
• Analyze large datasets to extract actionable insights and drive data-driven decision-making.
• Ensure the scalability and reliability of AI/ML solutions in a production environment.
• Stay up-to-date with the latest advancements in AI/ML technologies & LLMs and integrate them into our operations.
• Mentor and guide junior team members in coding & SDLC standards, AI/ML best practices and methodologies.

• Master's or Bachelors in Computer Science, Data Science, Machine Learning, or a related field, with a focus on engineering.
• Excellent API design and engineering experience with proven usage of API python frameworks Quart, Flask or FastAPI
• Proficiency in Python & async programming, with a strong emphasis on writing comprehensive test cases using testing frameworks such as pytest to ensure code quality and reliability
• Expertise with Index & Vector DBs such as Opensearch./ElasticSearch
• Extensive experience in deploying AI/ML applications in a production environment, with skills in deploying models on AWS platforms such as SageMaker or Bedrock.
• Champion of MLOps practices, encompassing the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models.
• Experience with generative AI models, including GANs, VAEs, or transformers. Experience with Diffusion models is a plus.
• Solid understanding of data preprocessing, prompt engineering, feature engineering, and model evaluation techniques.
• Proficiency in AI coding tools and editors such as Cursor, Windsurf or CoPilot
• Familiarity in machine learning frameworks such as TensorFlow, PyTorch, PyTorch Lightning, or Scikit-learn.
• Familiarity with cloud platforms (AWS) and containerization technologies (Docker, Kubernetes, Amazon EKS, ECS).

Preferred qualifications, capabilities, and skills

• Expertise in cloud storage such as RDS and S3
• Excellent problem-solving skills and the ability to work independently and collaboratively.
• Strong communication skills to effectively convey complex technical concepts to non-technical stakeholders.
• Proven experience in leading projects and teams, with a track record of successful project delivery.

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