Job Description:What is the opportunity?Our platform manages millions of devices across multiple operating systems, requiring exceptional performance, scalability, availability, and resilience. You will join the AI Platform Team, the group responsible for building foundational AI capabilities across the Omnissa product ecosystem.
As a Senior Data Scientist, you will lead and innovate within the data science team to drive significant advancements in our AI/ML and data analytics capabilities. This is a hands-on role, and you will be expected to develop AI/ML based solutions, work closely with cross-functional teams to solve complex business problems, and contribute to the company's vision through advanced analytics, machine learning, and artificial intelligence. You'll work closely with engineering and product teams to operationalize models across our cloud scale environment
while driving best in class ML engineering practices. Here's a breakdown:
- Lead the design and development of advanced data science and machine learning analytics models using structured, unstructured and semi-structured data.
- Work with engineers to design and implement scalable machine learning pipelines, covering all stages from data ingestion and feature extraction to training, testing, validation, inference, and continuous learning in production systems.
- Leverage key technologies and state-of-the-art tools necessary for exploring/querying data, visualization, and advanced analytics - distribution of key attributes, relationships between attributes, feature engineering, and statistical analyses.
- Be an expert in and lead the development of AI/ML solutions based on Large Language Models (LLMs), Retreival Augmented Generation (RAG), and AI Agents.
- Optimize ML models and pipelines for performance, scalability, reliability, and cost efficiency.
- Design and implement prompt engineering strategies to optimize the performance of LLM based applications.
- Collaborate with cross functional teams to integrate ML solutions into core platform features and services.
What will you bring to Omnissa?- 5+ years of experience in data science or machine learning engineering roles.
- Hands-on experience with one or more of the following areas is required; experience across multiple areas is strongly preferred: supervised and unsupervised learning, classification and regression, clustering, time-series analysis, anomaly detection, recommendation systems, reinforcement learning, information retrieval, and natural language processing (NLP).
- Highly proficient in Python and working knowledge of at least one other programming language such as Java, C++.
- Extensive experience with AI/ML frameworks and libraries such as Scikit-Learn, Numpy, Pandas, SciPy, Hugging Face Transformers.
- Hands-on experience with Large Language Models (LLMs), including finetuning, prompt engineering, and deployment.
- Knowledge of text embedding models and vector databases for Retrieval Augmented Generation (RAG) systems.
- Experience with orchestration frameworks (e.g., LangChain/LangGraph) to build AI agents and multi-agent systems.
- Familiarity with cloud platforms and tools such as AWS, Azure, of Google Cloud for development and deployment of scalable AI/ML models.
- Experience with distributed computing frameworks (e.g., Spark, Ray).
Location: Mountain View, CA or Atlanta, GA
Location Type: hybrid
Travel Expectations: None
Education: Bachelor's Degree preferred, or equivalent combination of education and relevant professional experience.
Compensation: The typical base salary for this role is between USD $146,287 - $304,750 per year and it may be eligible for participation in a corporate bonus program. Actual compensation offer may vary from posted hiring range based upon geographic location, work experience, education, skill level, or other relevant factors. In addition to competitive compensation, Omnissa offers a variety of benefits such as employee ownership, health insurance, 401k with matching contributions, disability insurance, paid-time off, growth opportunities, and more.
