Applied AI/ML Engineer-Vice President
Role details
Job location
Tech stack
Job description
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.
Requirements
- 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.
Benefits & conditions
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
