Staff Applied Scientist

Tekion

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.

• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.

• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.

• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.

• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekions position as a center of innovation.

• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.

• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.

• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI

Core Competencies & Technical Expertise

The successful candidate will demonstrate mastery in the following areas:

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.

• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
  

Deep Learning:

• Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.

• Extensive experience implementing advanced neural network architectures.

• Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g.,spaCy) methodologies.

• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.

Technical Proficiencies:

• Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.

• Proficiency with cloud computing platforms (GCP, Azure, AWS).

• Expertise in experimental design (A/B testing, causal inference).

• Proficient in version control systems (Git).

Required Qualifications

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.

• A minimum of 7 - 9 years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.

• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.

• Proven experience in programming, data manipulation, and building models in a business context.

• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.
  

Ideal Candidate Profile

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.

• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.

• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.

• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.

• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.

• A commitment to continuous personal and team development within a collaborative, high-performance culture.

Perks and Benefits

• Competitive compensation

• Generous stock options

• Medical Insurance coverage

• Work with some of the brightest minds from Silicon Valley s most dominant and successful companies