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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and optimizing AI solutions, with a strong focus on cognitive analytics, large-scale distributed systems, and advanced prompt engineering. Proficient in communicating complex AI concepts to non-technical stakeholders while driving measurable business outcomes.
Highest-signal resume keywords
Cognitive AnalyticsAI ModelingLarge-Scale Distributed SystemsAdvanced Prompt EngineeringGPU/CPU Architecture
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI Algorithm DevelopmentModel ServingPerformance AnalysisDebuggingC/C++ ProgrammingPython ProgrammingJava ProgrammingTensorFlowPyTorchOrchestration
Soft Skills
CollaborationCommunication
Industry Keywords
Generative AIDeep LearningPerformance TuningLatencyThroughput Bottlenecks
Tech Stack
Tools & technologiesDistributed SystemsJavaPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Design, develop and optimize AI, SLM/LLM, and Agentic solutions to resolve diverse real-world problems.
- Implement new algorithms and define APIs.
- Analyze functionality coverage to build larger, coherent toolsets and libraries.
- Collaborate with global teams to drive AI solutioning of business problems.
Requirements
What you’ll need- Four or more years of experience in cognitive analytics and AI Modeling.
- Must have experience working in a collaborative environment with global teams to drive AI solutioning of business problems and implement highly optimized AI algorithms.
- Must have hands-on experience in large-scale distributed systems capable of performing end-to-end AI training and SLM & LLM modeling including orchestration, fine-tuning, model serving in production environment (batch/real-time).
- Proven track record of designing, developing and deploying agentic solutions at scale with measurable results mapped to business goals.
- Must be able to communicate complex model designs and outcomes in business terms to a non-technical audience.
- Must have knowledge of GPU/CPU architecture and distributed computing.
- Must have working knowledge in advanced prompt engineering and optimizations techniques.
- Must have exposure to large-scale AI training, understanding of the compute system concepts (latency/throughput bottlenecks, pipelining, multiprocessing etc) and related performance analysis and tuning.
- Must have experience in Research and Development: Stay up-to-date with the latest advancements in generative AI, deep learning, and related fields.
- Must have good understanding and ability to explain both the code and the underlying math used in algorithms/models.
- Must have proficiency in programming languages such as C/C++, Python, Java, debugging, performance analysis and relevant AI libraries/frameworks (TensorFlow, PyTorch, etc).
Benefits
Comp & perks- Competitive salary
- Flexible work arrangements
- Professional development opportunities
