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Apply in 3 Minutes Senior AI Engineer
4 weeks ago
TheMathCompany or MathCo® is a global Enterprise AI and Analytics company trusted for data-driven decision-making by leading Fortune 500 and Global 2000 enterprises. Founded in 2016, MathCo builds custom AI and advanced analytics solutions focused on enterprise problem-solving through its innovative hybrid model. NucliOS, MathCo’s proprietary platform with pre-built workflows and reusable plug-and-play modules, enables the vision of connected intelligence at a lower TCO. For our employees, we foster an open, transparent, and collaborative culture with no barriers, making MathCo a great place to work. We provide exciting growth opportunities, value capabilities, and attitude over experience, enabling the Mathemagicians to ‘Leave a Mark’.
Responsibilities
- Responsible for designing, building, and maintaining scalable AI solutions
- Develop and implement advanced Generative AI solutions (LLMs, embeddings, retrieval techniques, prompt engineering)
- Ensure that data architectures and infrastructure can scale seamlessly as the data volume and complexity grow
- Lead, mentor, and develop a team of AI Engineers, fostering a collaborative and inclusive team environment
- Identify and address skill gaps, and provide opportunities for professional development
- Coordinate with stakeholders to gather requirements, set priorities, and define project timelines
- Ensure projects align with overall business objectives and data strategy
- Ensure data quality, integrity, and security across all data engineering projects
- Identify opportunities for process improvements and drive initiatives to enhance the efficiency and effectiveness of data operations
- Ability to build/drive reusable frameworks that can drive efficiency of the overall data system
- Manages conversation with the client stakeholders to understand the requirement and translate it into technical outcomes
Required Skills (Must have)
Tech:
- Experience of 4.5 - 7 years in development and deployment of scalable AI/ML solutions
- Has strong execution knowledge of Data Modeling, Databases in general (SQL and NoSQL), software development lifecycle and practices, unit testing, functional programming, etc
- Develop and implement advanced Generative AI solutions (LLMs, embeddings, retrieval techniques, prompt engineering)
- Design and optimize Retrieval-Augmented Generation (RAG) solutions
- Manage Databricks workflows, including job and cluster creation also Databricks API
- Apply data structures and algorithms knowledge, including multiprocessing and optimization techniques
- Utilize Python libraries (Pandas, Numpy, FastAPI) for data processing and API development
- Perform SQL optimization and database architecture design (schema creation, normalization, functions, triggers)
- Deploy and orchestrate AI models using Docker and Kubernetes
- Collaborate using GitHub for version control and team collaboration
- Work with cloud platforms for AI solution deployment and management (Azure, GCP, AWS)
- Utilize PySpark for data processing (optional)
- Basic understanding of CI/CD pipelines and deployment process
Non-Tech:
- Strong problem-solving skills with an ability to assess the financial impact of decisions, both in running the delivery team and delivering solutions to clients
- Proficient in written and verbal communication and able to hold conversations with mid-management-level clients
- Ability to recognize pragmatic alternatives vis-à-vis a perfect solution and get the delivery teams on board to pursue them, balancing time priorities with potential business impact
- Strong people skills, including conflict resolution, empathy, communication, listening, and negotiation
- Shows proficiency in providing technical guidance and provide leadership and mentorship to the delivery team
- Self-driven with a strong sense of ownership
Good to Have Skills
- Familiarity with data visualization tools and techniques
- Knowledge of data security and privacy practices
- Understanding of data governance and compliance frameworks
- Experience with graph databases and graph processing frameworks
- Experience with data virtualization and data federation techniques
- Proficiency in data profiling and data quality management
