Job Details

Join to apply for the AI & ML - Staff Scientist role at Signify Technology

Join to apply for the AI & ML - Staff Scientist role at Signify Technology

Job title: AI & ML - Staff Scientist

Job type: Permanent

Salary: $250,000 - $275000 + equity

Role Location: Los Altos, CA

Visa requirements: Candidates must be authorized to work in the United States

The Company

Our client, an emerging start-up, is building a revolutionary recommender system, utilizing Artificial intelligence, for the use of their Enterprise Clients. With this platform, hundreds of personalized campaigns can be generated and deployed in minutes, moving beyond static, rules-based segmentation and targeting. The platform is user-friendly, integrates seamlessly with major data and customer engagement tools, and optimizes internal resources. Founded by experts from Google, Meta, and Lyft, their team is driven by a vision to shift from static segmentation to real-time, ML-driven decision-making, delivering significant revenue improvements and cost reductions.

Role And Responsibilities

As a core member of the firm's Data Science team, you will shape the data science vision and roadmap while building and enhancing their Machine Learning models and Agentic AI products. Key responsibilities include:

• Designing, implementing, and researching machine learning algorithms to address growth and personalization challenges, with continuous fine-tuning and improvement.
• Developing AI-driven autonomous agents to execute complex workflows across diverse applications and objectives.
• Implementing and enhancing offline model evaluation methods.
• Analyzing large business datasets to extract insights and answer critical business questions using statistical or machine learning methodologies.
• Communicating data-driven insights and recommendations to product, growth, and data science teams at the client's customers.
• Staying current on ML research through literature reviews, conferences, and networking.
  
  

Job requirements:

• Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 7+ years of experience training, improving, and deploying ML models and developing production software systems (e.g., data pipelines, dashboards) at fast-growing technology companies.
• Proficiency in ML frameworks (TensorFlow, PyTorch, Jax) and the Python data science ecosystem (Numpy, SciPy, Pandas, etc.).
• Experience with LLMs, RAG, and information retrieval in building production-grade solutions.
• Expertise in recommender systems, feed ranking, and optimization.
• Knowledge of causal inference techniques and experimental design.
• Experience with cloud services for managing and consuming large-scale datasets.
• Thrives in ambiguity, with an ownership mindset and willingness to contribute beyond the role (e.g., product vision, strategic roadmap, engineering).
  
  

Benefits:

• Competitive salary and equity package.
• Comprehensive health, dental, and vision insurance.
• Flexible work environment with opportunities for hybrid work.
• Professional development budget for conferences, courses, and networking.
• Collaborative, innovative, and inclusive team culture.
  
  

Accessibility Statement:

Read and apply for this role in the way that works for you by using our Recite Me assistive technology tool. Click the circle at the bottom right side of the screen and select your preferences.

We make an active choice to be inclusive towards everyone every day.? Please let us know if you require any accessibility adjustments through the application or interview process.

Our Commitment To Diversity, Equity, And Inclusion

Signify's mission is to empower every person, regardless of their background or?circumstances, with an equitable chance to achieve the careers?they deserve. Building a diverse future, one placement at a?time.

Check out our DE&I page hereSeniority level

• Seniority levelMid-Senior level

Employment type

• Employment typeFull-time

Job function

• Job functionEngineering and Information Technology
• IndustriesStaffing and Recruiting

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