Senior AI Engineer MLOps
- Rapid7
- 5 - 8 years
- Pune
- 8 months ago
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Job Description
About the Role
Rapid7 is seeking a Senior AI Engineer to join our team as we expand and evolve our growing AI and MLOps efforts. You should have a strong foundation in applied AI R&D, software engineering, and MLOps and DevOps systems and tools. Further, you ll have a demonstrable track record of taking models created in the AI R&D process to production with repeatable deployment, monitoring and observability patterns. In this intersectional role, you will deftly combine your expertise in AI/ML deployments, cloud systems and software engineering to enhance our product offerings and streamline our platforms functionalities.
In this role, you will:
Interdisciplinary Collaboration - Collaborate closely with engineers and researchers to refine key product and platform components, aligning with both user needs and internal objectives.
- Actively contribute to cross-functional teams, focusing on the successful building and deployment of AI applications
Data Pipeline Construction and Lifecycle Management
- Contribute to and maintain data pipelines, manage the data lifecycle, and ensure data quality and consistency throughout.
Model Development, Validation, and Maintenance
- Help to build, validate, and continuously improve machine learning models, manage concept drift, and ensure the reliability of deployed systems.
Knowledge and Expertise Sharing
- Thoroughly document research findings, methodologies, and implementation details.
- Share expertise and knowledge consistently with internal and external stakeholders, nurturing a collaborative environment.
ML Deployment
- Implement, monitor, and manage ML services and pipelines within an AWS environment, employing tools such as Sagemaker and Terraform.
- Assure robust implementation of ML guardrails, leveraging frameworks like NVIDIA NeMo, and managing all aspects of service monitoring.
- Develop and deploy accessible endpoints, including web applications and REST APIs, while maintaining steadfast data privacy and adherence to security best practices and regulations
Software Engineering
- Contribute to the development of core API components to enable interactions with LLMs.
- Craft and optimize conversational interfaces, capitalizing on the capabilities of LLMs.
- Conduct API and interface optimization with a product-focused approach, ensuring performance, robustness, and user accessibility are paramount
Continuous Improvement
- Embrace agile development practices, valuing constant iteration, improvement, and effective problem-solving in complex and ambiguous scenarios.
The skills you ll bring include:
- A minimum of 5 years experience as a Software Engineer with 3-5 years focussed on gaining expertise in ML deployment (especially in AWS)
- A solid technical understanding in the following is required:
- building APIs and/or interfaces, paired with adept coding skills in Python and TypeScript
- containerization and DevOps
- CI/CD tooling, Docker, Kubernetes, and have prior experience developing APIs with Flask or FastAPI
- experience deploying LLMs, managing advanced compute resources like GPUs, and navigating data collection for metrics and fine-tuning from LLM-based systems
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- Demonstrate exemplary analytical and problem-solving capabilities, particularly in decomposing complex problems into manageable parts and devising innovative solutions
- Strong communication skills, with the capacity to convey intricate ideas effectively. Able to explain hard-to-understand topics to different audiences, working to build consensus, and writing up work clearly
- Maintain high standards of engineering hygiene, embracing best practices and an agile development mindset
- Bring a positive, can-do, solution-oriented mindset, welcoming the challenge of tackling the biggest problems with a bias for action
- Are persistent and consistent, being able to systematically tackle complex use cases head-on
- Enjoy working in a fast-paced environment, sometimes with multiple projects to juggle simultaneously
- Understand the highly iterative nature of AI development and the need for rigour. Appreciate the importance of thorough testing and evaluation to avoid silent failures
- Are a great teammate to help peers become stronger problem solvers, communicators, and collaborators
- Have a curiosity and passion for continuous learning and self-development
- Stay receptive to new ideas, listen to suggestions from colleagues, carefully considering and sometimes adopting them
- Realise the importance of wider ethical and risk considerations with AI
Experience with the following would be advantageous:
- Have previous experience with NLP and ML models, understanding their operational frameworks and limitations.
- Have previous experience deploying LLMs, managing advanced compute resources like GPUs, and navigating data collection for metrics and fine-tuning from LLM-based systems
- Possess proficiency in implementing model risk management strategies, including model registries, concept/covariate drift monitoring, and hyperparameter tuning.
- Experience in designing and integrating scalable AI/ML systems into production environments.
Job Classification
Industry: Law Enforcement / Security ServicesFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data Science & Machine Learning - OtherEmployement Type: Full timeContact Details:
Company: Rapid7Location(s): Pune+ View Contact
Keyskills: Publishing Compliance Coding Analytical SOC Data collection Data quality Risk management Operations Python
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