Overview
On Site
Hybrid
$0.1 hr
Full Time
Contract - Independent
Contract - W2
Skills
ARIMA
SARIMA
SARIMAX
XGBOOST
PROPHET
AI/ML
MACHINE LEARNING
M/L
LLM
NLP
MANAGER
ENGINEER
Job Details
Title: Data Scientist (Manager, Principal, Staff)
Location : Sunnyvale, CA or Bentonville, AR - Onsite
Duration : Fulltime
We are looking for Staff Engineers of Data Science, Principal Engineer of Data Science, Manager of Data Science.
For Staff Engineers of Data Science
Job description
Required skills
- Master's degree or PHD in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in analytics related field.
- Strong solution architecture mindset, with the ability to apply AI/ML technologies to solve complex business problems.
- Experience with training and inference of large-scale AI models such as Large Language Models (LLMs), multimodal models, and reasoning models.
- Knowledge of advanced model optimization techniques, including quantization, pruning, distillation, Low-Rank Adaptation (Lora), and Parameter-Efficient Fine-Tuning (PEFT) for cloud deployment.
- Solid understanding of LLMs and Genai ecosystems, including GPT, LLaMA, Mistral, Claude, Gemini, AWS Sonnet, and related frameworks/tools.
- Hands-on experience with RAG (Retrieval-Augmented Generation), AI agent development, and frameworks such as Lang Chain, Langgraph etc.,
Nice to have
- Experience with Big Data processing and feature engineering using Spark
- Experience with training machine learning models through Cloud Services including Google Cloud Platform and Microsoft Azure
- Hands on experience of designing and training large DL models on GPU
For Principal Engineer of Data Science
Responsibilities
- Develop LLM-powered intelligent experiences that interpret and generate insights from both tabular and unstructured data.
- Build and optimize personalized Q&A systems using large language models,enabling context-aware responses tailored to user needs.
- Design and enhance conversational talent recommendation systems, combining autonomous agent architectures with personalized recommendation algorithms.
- Advance traditional recommendation systems by evolving them from simple ranked lists to multi-topic, interactive experiences that better reflect user intent.
- Construct multi-agent intelligent workflows that translate natural language inputs into complex goal-directed task sequences.
- Collaborate within a highly cross-functional team, including data scientists,machine learning engineers, product managers, and UX designers.
- Partner with fellow data scientists to design, prototype, and iterate on AI/ML models and system architectures.
- Work closely with machine learning engineers to deploy, monitor, and optimize scalable AI/ML solutions in production environments.
- Collaborate with product managers to design intuitive user experiences, define feedback loops, and analyze user telemetry to guide product improvements.
- Engage in end-to-end AI/ML product development, from ideation to deployment, while continually expanding your technical and product skillset.
- Follow and help define robust development standards to ensure the creation of trustworthy, safe, and responsible AI systems.
- Contribute to internal and external AI/ML research through experimentation, whitepapers, and collaboration with the broader AI community.
Required Skills
- Proven experience deploying high-risk NLP applications in real-world, production environments such as those involving regulatory compliance, privacy, safety, or fairness.
- Demonstrated ability to advance and implement Trustworthy AI and Responsible ML practices, working cross-functionally with engineering, legal, policy, and product stakeholders across a large enterprise.
- Track record of mentoring and coaching junior data scientists, especially in navigating ambiguous or novel problem spaces. Strong applied machine learning experience, with solid foundational knowledge in statistics, optimization, and deep learning preferably gained at leading technology companies
(e.g., Google, Meta, Microsoft) or AI-first startups.
- Excellent communication skills with the ability to synthesize complex technical work into accessible insights for executive briefings, research publications, and external presentations.
- Advanced proficiency in Python and common ML/DS libraries such as NumPy, pandas, scikit-learn, as well as deep learning frameworks like TensorFlow, PyTorch.
- Experience designing and deploying scalable deep learning systems, including neural network architecture optimization, model distillation, quantization, or on- device inference.
- Strong understanding of machine learning infrastructure, including experience with Kubeflow, MLflow, Airflow is a plus.
Bonus Skills:
- Hands-on experience with Text-to-SQL or Text-to-Cypher based application, or the design of modern recommender systems.
- Experience developing or fine-tuning large language models (LLMs), including prompt engineering, retrieval-augmented generation (RAG), or open-weight model customization.
- Publication history in top-tier ML/NLP conferences such as NeurIPS, ICML, ACL, EMNLP, or ICLR.
For Manager of Data Science
Responsibilities
- Grow a team of domain experts of NLP, LLM , Timeseries Forecasting and recommendation systems in respective business domains in retail ; e-commerce.
- Drive execution of developing models and systems
- Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
- Remain up to date on ongoing research and development activities in the team
- Work with data scientists to design, architect, and build AI/ML/DL model and model systems.
- Work with machine learning engineers to deploy, operate, and optimize scalable solutions
Required Skills
- Experience in NLP, LLM, Timeseries, Traditional ML techniques
- Experience in data science and machine learningfor retail ; e-commerce
- Experience in managing a mid-size internal team of data scientists and MLEs
- Experience leading and completing cross-functional projects
- Strong organizational skills including prioritizing, scheduling, time management, and meeting deadlines
- Strong influencing and interpersonal skills
- Detail and results-oriented with sense of urgency
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