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Researches and evaluates emerging AI models and technologies to guide enterprise strategy, producing benchmarks and recommendations on adoption and deployment.
Lead AI research to evaluate and benchmark LLMs and AI platforms, translating findings into strategic recommendations for enterprise adoption and investment decisions.
Build and deploy AI/ML models on Azure, integrating with Microsoft services like Teams and Graph API using Python, PyTorch, and LangChain.
Build and deploy ML systems for sports-tech products, including recommender engines, NLP, LLM apps, and semantic search, using Python, PyTorch, and SQL at scale.
Intern researching and implementing AI/ML algorithms for embedded systems and edge devices using C/C++ and Python, with a focus on time-series models.
Build enterprise-grade Generative AI and AI/ML platform services, APIs, and agentic workflows using Python, FastAPI, Kafka, and Kubernetes to accelerate AI adoption for clients in banking and consumer sectors.
Design and deploy production-grade AI systems, including agentic workflows and GenAI, to drive measurable business impact in digital banking and lending.
Build AI-powered assistants and agents to automate IT infrastructure operations, troubleshooting, and engineering productivity using Python, RAG, and cloud-native tools.
Build and scale AI agents and foundation models for drug discovery, integrating biological data and MLOps pipelines to accelerate therapeutic research.
Senior ML Engineer builds and scales recommendation systems, productionizing models with PySpark, Airflow, and AWS SageMaker for real-time and batch inference.
Build and deploy AI-powered applications using Azure AI services, RAG, and agentic frameworks like LangGraph to create intelligent, automated solutions for clients.
Build and maintain low-level drivers and firmware for NVIDIA’s Deep Learning Accelerator hardware, optimizing performance for AI workloads in self-driving cars, gaming, and content creation.
Build, deploy, and monitor ML models and AI systems (including multi-agent setups) to predict customer behavior and power financial products at a LATAM fintech platform.
Research and build AI/ML models to detect and evaluate security incidents from behavioral data, applying modern architectures like transformers to cybersecurity challenges.
Build and deploy large-scale AI/ML models to optimize Amazon Prime’s customer experience using GenAI, LLMs, and reinforcement learning on TB-scale data.
Build and optimize distributed training infrastructure for GenAI models on AWS Trainium using PyTorch/JAX, tuning compiler, runtime, and parallelism to maximize throughput and hardware utilization.
Lead a team building and optimizing scalable ML training platforms on AWS/Kubernetes, focusing on GPU workloads, performance tuning, and Gen AI/LLM pipelines while enforcing enterprise governance and security standards.
Build and productionize secure, scalable AI/ML and GenAI solutions using Python, LLMs, and agentic frameworks to drive measurable business outcomes at a major bank.
Design and implement AI/ML solutions—including LLM-powered workflows and agent-based automation—to streamline classified-data analysis and support rapid decision-making for national security missions.
Build and maintain ML infrastructure and data pipelines to operationalize AI models for drug-quality oversight in a regulated healthcare environment, using Python, cloud platforms, and MLOps practices.
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