Distinguished Data Scientist

Jobtailor; California (MO); On-site; USD 180,000 - 260,000; Full time

Job summary

Jobtailor is seeking a senior ML leader to design and deploy production-grade AI systems, including agentic and reinforcement learning capabilities. You will mentor engineers, shape architecture, and drive long-term AI strategy across cloud platforms and NLP pipelines.

The role focuses on translating complex analytics into business value, with emphasis on end-to-end development, evaluation, and governance of AI deployments.

Qualifications

• Strong background in ML algorithms and large-scale AI systems.
• Experience with NLP pipelines, embeddings and RAG concepts.
• Hands-on production ML, MLOps, and cloud platforms (SageMaker/Vertex AI).
• Ability to translate complex analyses into business impact.

Responsibilities

• Build and deploy production ML systems end-to-end including data pipelines and feature stores.
• Provide technical vision and lead development in agentic AI and reinforcement learning.
• Architect and deploy large-scale AI systems and autonomous agents.
• Design evaluation frameworks for task completion and multi-step reasoning.
• Deploy NLP pipelines using semantic similarity, embeddings, and vector search.
• Lead projects from framing to rollout and mentor staff.

Skills

Machine Learning

Python Programming

Deep Learning (PyTorch)

NLP & Transformers

Cloud ML (SageMaker / Vertex AI)

MLOps & Docker

Education

Bachelor's degree in Statistics, Economics, Analytics, Mathematics, CS or related field

Master's degree with 4+ years experience

PhD or publications preferred

Tools

Docker

LangChain

FAISS

BigQuery

Vertex AI

SageMaker

Python tooling

Job description

• Build and deploy production ML systems end-to-end, including data pipelines, feature stores, model training, serving layers, monitoring, and feedback loops
• Provide technical vision and lead advanced development in agentic AI, reinforcement learning, and simulation
• Architect and deploy large-scale AI systems and autonomous AI agents, including conversational assistants, predictive agents, and multi-agent orchestration systems
• Design agentic evaluation frameworks benchmarking task completion, code quality, and multi-step reasoning accuracy
• Deploy enterprise-scale NLP pipelines using semantic similarity, embeddings, and vector search
• Lead projects through problem framing, modeling, prototyping, production architecture, and rollout
• Author and review technical designs and standards and present findings to senior leadership
• Mentor senior scientists and engineers on modeling, feature engineering, and experimentation
• Establish best practices for model validation, experimentation, and safe AI deployment
• Influence roadmap prioritization and long-term AI and simulation strategy
• Present insights with data visualization, quantified business impact, and confidence intervals

Requirements

• Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 6 years’ analytics experience; OR master’s degree and 4 years’ experience; OR 8 years’ experience in an analytics or related field
• Deep expertise in ML algorithms including XGBoost, CatBoost, LightGBM, Random Forest, and AutoML
• Deep learning expertise with PyTorch and transformer architectures
• Production experience with NLP, BERT, SBERT, FAISS, RAG, computer vision, YOLO, CLIP, and time series forecasting with ARIMA and Prophet
• Hands-on experience building and orchestrating multiple AI agents with LangChain, RAG, tool integration, and memory management
• Proficiency with AWS SageMaker and GCP, including Vertex AI, BigQuery, and BigQuery ML
• Strong Python skills with Pandas, NumPy, and Scikit-learn
• Experience with Docker and MLOps practices
• Advanced statistical analysis, experiment design, and causal inference
• Experience deploying production-grade AI systems at scale
• Ability to translate complex analytical results into clear business recommendations
• Preferred: master’s degree and 8+ years’ data science or machine learning experience
• PhD, publications or peer review, Python/Spark/Scala/R assessments, open-source frameworks, and accessibility knowledge are preferred

Core Competencies

Demonstrates expertise in building and deploying production ML systems, including advanced development in agentic AI and reinforcement learning. Proficient in architecting large-scale AI systems and deploying enterprise-scale NLP pipelines while mentoring teams and influencing strategic direction.

Highest-signal resume keywords

• Machine Learning Algorithms
• Deep Learning with PyTorch
• Natural Language Processing
• AWS SageMaker and GCP
• Python Programming

ATS Optimization Keywords

Hard Skills

• XGBoost
• CatBoost
• LightGBM
• Random Forest
• AutoML
• BERT
• FAISS
• Docker
• Statistical Analysis
• Causal Inference

Soft Skills

• Mentoring
• Communication
• Problem Framing

Industry Keywords

• Machine Learning
• AI Systems
• NLP Pipelines
• Data Visualization
• Experiment Design

Tools & Technologies

• AWS SageMaker
• GCP
• Vertex AI
• BigQuery
• LangChain