Job Description

Senior Machine Learning Engineer – (via Shields Group Search)

📍 Onsite – New York City (Flatiron District)

💼 Full-Time | Salary: $140,000–$160,000 + Equity

Shields Group Search is partnering with a fast-growing, VC-backed startup modernizing operations in a legacy B2B industry. The company recently launched V1 of its product and has grown revenue 10x in just five months. We’re now helping them hire a Senior Machine Learning Engineer to lead development of deep learning systems powering their core document intelligence engine.

Background

Our client is building the next-generation operating system for suppliers and contractors in a large, underserved industrial sector. Backed by top-tier VCs and industry angels, they’ve shipped an MVP, found clear product-market fit, and are scaling rapidly through 2025.

They’re looking for a Senior Engineer to lead the development of deep learning models that power their document understanding engine. In this role, you’ll architect training pipelines, design and adapt models for complex vision tasks, and help shape the direction of their ML stack as they scale. You’ll work closely with the CTO and product team to take research ideas from concept to production and play a key role in growing the ML function across both technology and process.

This role is ideal for someone who enjoys working with models under the hood, building and adapting training workflows, and applying research ideas to novel engineering challenges. The work involves much more than inference—this team owns training workflows, evaluation systems, and robust engineering around applied ML.

Responsibilities

• Model Training & Development : Design and train deep learning models for layout analysis, OCR, object detection, and related tasks. In some cases, you’ll extend or adapt existing architectures; in others, you’ll help design custom approaches from the ground up.
• Data Management : Design annotation workflows, manage labeled datasets, and develop strategies for efficient data selection and bootstrapping.
• Evaluation and Monitoring : Build robust metrics, monitor production model performance, and proactively identify failure modes and areas for improvement.
• Collaboration and Integration : Work closely with the engineering team to integrate models into our product and infrastructure. Participate in architecture and roadmap decisions.

What We’re Looking For

We’re looking for someone with a strong foundation in deep learning and a passion for building systems that go beyond the notebook. You should feel confident implementing training logic, experimenting with model internals, and debugging the kinds of real-world issues that arise when pushing ML into production.

We’re seeking someone who understands deep learning at its core and enjoys turning ideas into working, production-ready systems. This role is a great fit if you enjoy getting deep into PyTorch, working across the full ML stack, and solving open-ended modeling problems.

Required Qualifications

• Master's degree or PhD in Computer Science, Electrical Engineering, or other relevant field with main focus on machine learning.
• Proven ability to implement and adapt techniques or architectures from academic or industry literature.
• Proven track record tackling novel ML challenges in the field of Deep Learning.
• 4+ years of experience developing deep learning models in PyTorch.
• 2+ years of experience taking models from research to production in a startup or fast-paced environment.
• Proven experience designing training workflows and evaluating tradeoffs across model design, performance, and data quality.
• Demonstrated ability to work autonomously on open-ended problems and contribute to broader product or system design.

Nice to Have

• Experience with active learning setups.
• Ability to implement CV algorithms in a low-level language (C).
• Strong understanding of traditional CV techniques (component analysis, template matching, SIFT, etc.)
• Experience with OpenCV
• Published research developing SOTA computer vision models.
• Experience building continual learning or periodic retraining pipelines for production CV applications.
• Experience with deployment and monitoring pipelines for ML systems.

Compensation & Benefits

• Salary : $140,000–$160,000, dependent on experience
• Equity : Meaningful early-stage equity package
• Benefits : Comprehensive medical, dental, and vision coverage
• Perks : Free lunches and dinners provided regularly

This is a full-time onsite role located in New York City’s Flatiron District, just minutes from Madison Square Park and Union Square. You’ll work closely with a high-caliber technical team and play a pivotal role in shaping both the ML stack and the future of the product.

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