Senior Machine Learning Engineer / Researcher (NYC) at Modal

New York, New York, United States

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$250,000 – $300,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, TechnologyIndustries

Requirements

Master’s or PhD in Computer Science, Machine Learning, Statistics, Applied Math or equivalent experience
Solid understanding of ML fundamentals: supervised & unsupervised learning, deep learning, model evaluation metrics, deployment, inference latency trade-offs
Familiarity with knowledge representation and retrieval: building or leveraging knowledge graphs, embeddings, and memory systems to support contextual inference and long-term model learning
5+ years of hands-on experience building machine learning models in production environments
Experience deploying models at scale in production (AWS/GCP/Azure)
Experience with data engineering (ETL pipelines, feature stores, large datasets) and production-grade MLOps (CI/CD, monitoring, retraining workflows)
Bonus / preferred: Published research or open-source contributions
Bonus / preferred: Experience with genAI (LLMs, diffusion models), computer vision, multimodal ML
Bonus / preferred: Knowledge of prompt engineering, RAG, embeddings
Ownership mentality (no task is too small)
Deep understanding of system architecture and design patterns
Excellent communication skills and a collaborative mindset

Responsibilities

Design and implement knowledge graph or memory systems to enable contextual retrieval, reasoning, and persistent knowledge for the core Highlight application
Research, prototype and deploy state-of-the-art machine learning text and OCR models (e.g., transformer architectures, computer vision, time series forecasting, reinforcement learning)
Build pipelines for data ingestion, feature engineering, model training, evaluation, and deployment
Work on productionizing models: monitoring, scalability, latency, retraining, A/B testing, and model lifecycle management
Develop infrastructure and tooling to support ML experimentation and production (e.g., model serving, MLOps, observability)
Collaborate with cross-functional partners (product managers, software engineers, UX researchers) to integrate ML features into product flows
Keep abreast of latest ML/AI research, propose novel approaches, publish (internally or externally) when appropriate
Participate in architecture discussions & technical direction for ML/AI at the company

Skills

Machine Learning

Knowledge Graphs

Transformers

OCR

Computer Vision

Time Series Forecasting

Reinforcement Learning

Data Ingestion

Feature Engineering

MLOps

Model Serving

A/B Testing

Scalability

Modal

Employee training and skill development platform

About Modal

Modal Learning focuses on improving employee performance through skill development for businesses. Their main product, the Modal Mastery Platform, uses active learning techniques, including live cohort sessions, labs, and one-on-one coaching, to help employees engage with the material effectively. Unlike competitors, Modal Learning offers a subscription model that provides structured eight-week training programs, aligning skill development with organizational goals. The company's goal is to empower employees and help organizations retain talent by providing clear career development paths.

San Francisco, CaliforniaHeadquarters

2021Year Founded

$30.8MTotal Funding

EARLY_VCCompany Stage

Consulting, EducationIndustries

51-200Employees

Risks

Competition from established players and emerging startups could dilute Modal's market share.

Focus on data and AI may limit appeal to companies seeking broader skill development.

Economic downturns could reduce corporate spending on employee training, impacting revenue.

Differentiation

Modal offers personalized technical skills training with on-demand coaching.

The platform uses cohort-based learning to enhance engagement and retention.

Modal's strategic skills planning aligns training with business goals.

Upsides

Increased demand for personalized learning experiences boosts Modal's market potential.

Growing emphasis on data and AI skills aligns with Modal's course offerings.

Subscription model provides steady revenue and predictable growth for Modal.

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