Staff Applied Scientist @ Cohesity

AI & Machine Learning (3)
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AI & Machine Learning (3)

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Cohesity is the leader in AI-powered data security. Over 13,600 enterprise customers, including over 85 of the Fortune 100 and nearly 70% of the Global 500, rely on Cohesity to strengthen their resilience while providing Gen AI insights into their vast amounts of data. Formed from the combination of Cohesity with Veritas’ enterprise data protection business, the company’s solutions secure and protect data on-premises, in the cloud, and at the edge. Backed by NVIDIA, IBM, HPE, Cisco, AWS, Google Cloud, and others, Cohesity is headquartered in Santa Clara, CA, with offices around the globe.

We’ve been named a Leader by multiple analyst firms and have been globally recognized for Innovation, Product Strength, and Simplicity in Design , and our culture.

Want to join the leader in AI-powered data security?

Cohesity is looking for a Staff Applied Scientist to spearhead advanced modeling, generative AI, and agentic workflows. This role combines deep expertise in statistical and machine learning methodologies ranging from causal inference and time-series forecasting to reinforcement learning with hands-on development of transformer-based LLMs, semantic search, and scalable AI system architectures. You’ll architect production-ready platforms, validate models through rigorous experimentation, and mentor a team to execute Cohesity’s AI vision.

Staff Applied Scientist will lead Cohesity’s efforts in NLP, generative AI, agentic development, and advanced data science modeling, driving design, validation, and deployment of complex algorithms and scalable AI platforms. You will translate business objectives into robust statistical and ML solutions, overseeing end-to-end experimentation, model governance, and performance optimization.

HOW YOU'LL SPEND YOUR TIME HERE:

Advanced Modeling & Algorithm Development

Lead development of predictive and prescriptive models—including deep learning, reinforcement learning, time-series forecasting, and causal inference pipelines—ensuring scientific rigor and production readiness.
Design and execute statistical experiments and A/B tests, establishing robust validation frameworks and ensuring reproducibility.

Experimentation & Performance Optimization

Design and implement robust experimentation frameworks—including A/B testing and causal inference methods—to evaluate AI-driven features and optimize product decisions.
Oversee performance profiling, benchmarking, and resource-efficient deployment strategies to meet strict latency and cost targets.

Generative AI & NLP

Develop and fine-tune transformer-based LLMs (e.g., using LoRA, QLoRA, and full fine-tuning techniques) to optimize performance for domain-specific tasks.
Implement Reinforcement Learning with Feedback (RLF) or Human Feedback (RLHF) to improve response quality and alignment with user intent.
Optimize training and inference workloads using GPU acceleration (CUDA) and explore model deployment using NVIDIA Inference Microservices (NIM) for scalable, low-latency serving.
Orchestrate multi-agent workflows and tool use with frameworks such as LangChain and OpenAI's Operator.
Integrate retrieval-augmented generation (RAG) and semantic search capabilities using vector databases like Pinecone, Weaviate, or Milvus.
Drive end-to-end delivery of customer-facing AI solutions by leveraging enterprise data catalogs to builddomain-specific LLMs, enabling context-aware responses grounded in structured and unstructured data.

System Architecture & Performance

Architect scalable, distributed AI platforms leveraging cloud/serverless technologies (AWS Lambda, Azure Functions) and GraphQL APIs for real-time inference.
Drive performance profiling, benchmarking, and resource-efficient deployment strategies to meet strict latency and cost targets.

Cross-Functional Collaboration

Partner with Product, Marketing, Finance, and Engineering teams to build scalable data pipelines and real-time dashboards that deliver actionable insights.
Translate complex modeling and AI concepts into clear narratives and presentations for stakeholders across the organization.

Mentorship & Leadership

Mentor and coach data scientists and engineers through design reviews, pair programming, and career development.
Establish best practices in model governance, data privacy, and ethical AI, and drive their adoption across teams.

WE'D LOVE TO TALK TO YOU IF YOU HAVE MANY OF THE FOLLOWING:

Master’s or Ph.D. in Computer Science, Statistics, Machine Learning, or a related quantitative field.
15+ years in data science/AI roles with at least 3 years leading large-scale AI or data science modeling initiatives in production environments.
Expert proficiency in Python and software engineering best practices; Golang or Java experience is a plus.
Hands-on with TensorFlow, PyTorch, and other deep learning frameworks; proven track record with transformer-based LLMs.
Deep expertise in statistical modeling, machine learning algorithms, and MLOps frameworks for model lifecycle management.
Familiarity with AI ethics, governance, and data privacy frameworks (e.g., EU AI Act, IEEE Trustworthy AI) .
Publications or patents in machine learning, data science, or AI domains.
Experience scaling AI solutions in high-growth or startup environments under tight timelines.

Data Privacy Notice for Job Candidates:

For information on personal data processing, please see our Privacy Policy.

Equal Employment Opportunity Employer (EEOE)

Cohesity is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status or any other category protected by law.

If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process, or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact us at 1-855-9COHESITY or [email protected] for assistance.

In-Office Expectations

Cohesity employees who are within a reasonable commute (e.g. within a forty-five (45) minute average travel time) work out of our core offices 2-3 days a week of their choosing.

Interested candidates based outside of the designated areas are welcome to apply, provided they have the right to work in the job location.

Staff Applied Scientist

Cohesity

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