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Nooks

Applied Machine Learning Engineer

Nooks · San Francisco, CA

  • On site
  • Full-time
  • $240,000 / year
  • San Francisco, CA

Job highlights

  • Implement ML features for AI sales assistant platform.
  • Train production models to enhance accuracy.
  • Align technical strategy with business needs.
  • Work with real-time audio AI and LLMs.
  • Collaborate on ambitious AI product vision.

About the role

About Nooks.ai

Nooks is the AI Sales Assistant Platform (ASAP) that automates the busywork so reps can focus on the human part of selling and generate more sales pipeline. Nooks has helped thousands of sales reps hit quota, saved customers hundreds of thousands of hours, and powered hundreds of millions of dollars in pipeline. Nooks is loved by sales teams at companies like Hubspot, Rippling, and hundreds more.

We’re a team of high performers raising over $70M from top VCs, including Kleiner Perkins, which made its first sales-tech investment in over 10 years by investing in Nooks. Over the past two years, we’ve grown ARR by 4x and then 3x, and we plan to 3x it again this year.

For more information, visit Nooks.ai.

The Role

We have an ambitious product vision in a nascent area - AI-powered realtime collaboration - so there are a ton of interesting technical challenges on our roadmap. This is a role focused on implementing ML features into Nooks. Our ideal candidate will have prior experience working in industry for a business where ML is a core part of the offering.

Responsibilities will include training production models to improve their accuracy for specific sales use cases. You will align our technical strategy with performance, cost and feasibility considerations.

Examples of Engineering Problems You May Touch

  • Realtime audio AI & precision/recall/latency tradeoffs (algorithms & models): Utilize audio data, transcription, silence detection, and other signals to detect voicemail, human, or dial tree. This involves LLM embeddings, few-shot learning, data labeling, and continuous monitoring of model performance.
  • Smart call funnels & playbooks (data wrangling, backend eng, GPT-3, UX): Analyze conversation data to identify points where reps get stuck, tough questions, and program playbooks to standardize best practices using GPT-3 and other LLMs.
  • Conversation embeddings & markov models (ML modeling): Analyze call structures, predict prospect responses, and generate conversation embeddings using LLMs to cluster similar patterns and predict conversation direction.

Requirements

  • Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field.
  • 3+ years of industry experience, including 2+ years training and deploying ML models in production.
  • Full stack ML Eng chops: proficiency in general purpose programming languages such as Python/Javascript, and with libraries like TensorFlow, PyTorch, Keras, scikit-learn etc.
  • Expertise in areas like NLP, Deep Learning, Anomaly Detection, Transformers and Large Language Models.

Nice to Haves

  • Background in an analytical field like heuristics, data science &/or statistics.
  • Prior experience working in both startup and research environments.

Compensation & Benefits

We offer competitive compensation because we want to hire the best people and reward them for their contributions to our mission. We pay all employees competitively relative to market. The target salary range for this role is $140,000 - $240,000. On top of base salary, we also offer equity, generous perks, and comprehensive benefits.

Equal Employment Opportunity Statement

Nooks is an equal opportunity employer committed to fostering a diverse and inclusive workforce. We believe in providing equal employment opportunities to all individuals regardless of race, color, religion, gender, gender identity, sexual orientation, national origin, age, disability, veteran status, or any other characteristic protected by law. Nooks does not discriminate in hiring, promotion, compensation, or any other employment practices, and we are committed to ensuring a workplace that is free from discrimination, harassment, and retaliation. We encourage individuals from all backgrounds to apply and join our team.

Key skills/competency

  • Machine Learning
  • Python
  • Deep Learning
  • NLP
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Large Language Models
  • Production ML
  • Data Science

Skills & topics

  • Applied Machine Learning Engineer
  • Machine Learning
  • Python
  • Deep Learning
  • NLP
  • TensorFlow
  • PyTorch
  • Large Language Models
  • Production ML
  • Data Science
  • AI
  • SalesTech
  • Software Engineer
  • ML Engineer
  • Computer Science
  • Data Science
  • Heuristics
  • Statistics

How to get hired

  • Tailor your resume: Highlight experience with Python, ML libraries (TensorFlow, PyTorch), NLP, and deploying models.
  • Showcase production ML skills: Emphasize your 2+ years of experience training and deploying ML models in a business setting.
  • Quantify achievements: Use numbers to demonstrate your impact in previous roles.
  • Prepare for technical interviews: Be ready to discuss ML concepts, algorithms, and your project experience.
  • Research Nooks.ai: Understand their AI Sales Assistant Platform and product vision.

Technical preparation

Practice Python coding challenges.,Review ML algorithms and tradeoffs.,Study NLP and LLM concepts.,Prepare to discuss production ML systems.

Behavioral questions

Describe a challenging ML project.,How do you handle production issues?,Discuss collaborating with sales teams.,Explain aligning strategy with feasibility.

Frequently asked questions

What is the target salary range for the Applied Machine Learning Engineer role at Nooks?
The target salary range for this role at Nooks is $140,000 to $240,000 annually, in addition to equity, generous perks, and comprehensive benefits.
What are the key technical skills required for this Applied Machine Learning Engineer position?
Key technical skills include proficiency in Python/Javascript, ML libraries like TensorFlow, PyTorch, Keras, scikit-learn, and expertise in NLP, Deep Learning, Anomaly Detection, Transformers, and Large Language Models.
Does Nooks.ai offer remote work for this Applied Machine Learning Engineer role?
The job description does not explicitly state the work arrangement. Based on typical industry practices for highly collaborative roles and the mention of a physical product (ASAP), it is likely an on-site or hybrid role, but candidates should inquire for clarification.
What is Nooks.ai's stance on equal employment opportunity for this Applied Machine Learning Engineer job?
Nooks is an equal opportunity employer committed to a diverse and inclusive workforce, providing equal opportunities regardless of race, color, religion, gender, sexual orientation, national origin, age, disability, or veteran status.
What kind of industry experience is Nooks looking for in an Applied Machine Learning Engineer candidate?
Nooks seeks candidates with 3+ years of industry experience, specifically including at least 2 years of training and deploying ML models in a production environment, ideally in a business where ML is a core offering.
What are some examples of the engineering problems an Applied Machine Learning Engineer might work on at Nooks?
Engineers may work on real-time audio AI with latency tradeoffs, developing smart call funnels using LLMs, and creating conversation embeddings and Markov models to analyze call dynamics.
What educational background is preferred for the Applied Machine Learning Engineer position?
A Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a closely related field is required for this role.