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Entry Level Computer Vision Deep Learning Engineer Jobs in Byram, CT

Optiver

Machine Learning Research Engineer

New York, NY · On-site

$200K/yr

Conduct innovative research on deep learning for price forecasting * Build scalable and robust ... Comprehensive health, mental, dental, vision, disability, and life coverage * 25 paid vacation days ...

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Entry Level Computer Vision Deep Learning Engineer information

See Byram, CT salary details

$53.9K

$135K

$152.7K

How much do entry level computer vision deep learning engineer jobs pay per year?

As of Jul 10, 2026, the average yearly pay for entry level computer vision deep learning engineer in Byram, CT is $134,978.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,900.00 and $146,100.00 per year, depending on experience, location, and employer.

What types of projects do entry-level Computer Vision Deep Learning Engineers typically work on, and how is their work structured within a team?

As an entry-level Computer Vision Deep Learning Engineer, you can expect to contribute to projects like object detection, image classification, and model optimization for real-world applications. Your tasks may include data preprocessing, training and evaluating neural networks, and writing code to integrate models into products or pipelines. You'll often collaborate closely with senior engineers, data scientists, and product managers, typically working in agile teams where regular code reviews and knowledge sharing are common. This collaborative environment not only helps you learn best practices but also provides opportunities to gradually take on more responsibility as your skills develop.

What does an Entry Level Computer Vision Deep Learning Engineer do?

An Entry Level Computer Vision Deep Learning Engineer works on developing and implementing algorithms that allow computers to interpret and understand visual information from the world, such as images or videos. They typically use deep learning techniques, especially neural networks, to build models for tasks like object detection, facial recognition, and image classification. Their responsibilities may include data preprocessing, model training and evaluation, writing code (often in Python), and collaborating with senior engineers on real-world projects. This role is ideal for those who have a strong foundation in machine learning, programming, and mathematics, but are just starting their careers in the field.

What are the key skills and qualifications needed to thrive as an Entry Level Computer Vision Deep Learning Engineer, and why are they important?

To thrive as an Entry Level Computer Vision Deep Learning Engineer, you need a solid understanding of computer vision fundamentals, deep learning concepts, and programming skills in languages like Python, along with a relevant degree in computer science, engineering, or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience with OpenCV, and knowledge of version control systems like Git are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate within teams and tackle complex challenges. These skills and qualities are crucial for developing, deploying, and optimizing computer vision solutions that meet real-world business needs.
Entry Level Computer Vision Deep Learning Engineer jobs near you

Senior Machine Learning Engineer - Enrichment & Content Intelligence

Spotify

New York, NY • On-site

$184K - $262K/yr

Other

Medical, Retirement, PTO

Re-posted 13 days ago

Job description

The Experience team designs Spotify's consumer experience-end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints-from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.
The Enrichment & Content Intelligence team sits within Content Platform in the Experience Mission. We build the metadata-resolution and content-enrichment infrastructure that powers how Spotify understands music and video content at global scale. Our systems help answer foundational questions across the platform: which tracks are the same recording, which music videos match which audio tracks, who wrote and performed a song, and how content relationships connect across Spotify's catalog.
Our infrastructure powers products and experiences used by millions of listeners, artists, and creators every day. From recommendations and charts to royalties and artist tooling, the work we do directly shapes how content is understood and surfaced across Spotify.
We're looking for a Senior Machine Learning Engineer to help evolve the machine learning systems behind Recording Groups, Music Video Resolution, SongDNA, and the Music Knowledge Graph. This role sits at the intersection of multimodal machine learning, entity resolution, and production-scale engineering, with opportunities to work across audio, video, and metadata understanding problems at massive scale.
What You'll Do
  • Own and evolve large-scale ML pipelines powering Spotify's content-resolution systems
  • Lead development of multimodal embedding frameworks supporting multimodal understanding, music video matching, SongDNA
  • Improve entity-resolution systems across music and video content, helping Spotify better understand relationships between recordings, versions, and content formats
  • Design and run experiments to improve precision, recall, and overall content-quality outcomes using offline evaluation, golden datasets, A/B testing, and impact analysis
  • Build scalable ML evaluation and monitoring infrastructure, including standardized datasets, retraining workflows, and continuous improvement systems
  • Contribute to the evolution of the Music Knowledge Graph by improving production ML capabilities, observability, and model lifecycle management
  • Partner closely with Product Managers, Data Scientists, and engineering teams across Content Platform and the wider Experience Mission
  • Help shape technical strategy for the squad and contribute to long-term ML direction across the product area
  • Mentor engineers and contribute to a strong culture of technical collaboration and experimentation

Who You Are
  • You have solid experience building, deploying, and maintaining machine learning systems in production at scale
  • You have strong experience training, evaluating, and operating ML models using modern frameworks such as PyTorch or TensorFlow
  • You have experience working with multimodal machine learning systems across audio, computer vision, text embeddings, or related domains
  • You understand entity resolution, deduplication, record linkage, or large-scale matching problems, ideally across multiple content modalities
  • You know how to design evaluation systems that balance model quality, operational performance, and real-world impact
  • You are experienced working with large-scale distributed data processing systems and ML infrastructure
  • You communicate effectively across engineering, product, and data science stakeholders
  • You are comfortable leading technical initiatives and influencing engineering direction within a team
  • Experience with Scio, Dataflow, Flyte, BigQuery, or similar distributed processing frameworks is a plus
  • Experience with Scala is a plus
  • Experience with computer vision, video understanding, multimodal embeddings, or recommendation systems is a strong plus

Where You'll Be
  • This role is based in New York City
  • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

The United States base range for this position is $184,049-262,928 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice

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