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Deep Learning Engineer Jobs in Boston, MA (NOW HIRING)

Roberts Recruiting

Machine Learning Engineer

Boston, MA · On-site

As a machine learning engineer, you will develop natural language processing systems that help our ... Broad knowledge of machine learning and deep learning models and its applications using standard ...

E Ink

Deep Learning Researcher 1900S-2

Billerica, MA · Hybrid

$130K - $160K/yr

S. + 4 years' experience) in Physics, Applied Math, Computer Science, Electrical Engineering, or related field. * Demonstrated research experience in deep learning with a track record of innovation.

E Ink

Deep Learning Researcher 1900S-2

Billerica, MA · On-site

$130K - $160K/yr

S. + 4 years' experience) in Physics, Applied Math, Computer Science, Electrical Engineering, or related field. * Demonstrated research experience in deep learning with a track record of innovation.

Beacon Biosignals

Algorithm Engineer

Boston, MA · On-site +1

Beacon Biosignals is seeking a Machine Learning engineer! At Beacon, we've found that cultural and ... Enhance our internal deep learning and machine learning tools to boost team efficiency, introduce ...

Beacon Biosignals

Algorithm Engineer

Boston, MA · On-site +1

Beacon Biosignals is seeking a Machine Learning engineer! At Beacon, we've found that cultural and ... Enhance our internal deep learning and machine learning tools to boost team efficiency, introduce ...

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Deep Learning Engineer information

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$41.3K

$125.9K

$208K

How much do deep learning engineer jobs pay per year?

As of Jul 8, 2026, the average yearly pay for deep learning engineer in Boston, MA is $125,875.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,200.00 and $164,600.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior Deep Learning Engineer or AI research director, often involving advanced skills in machine learning frameworks, data modeling, and large-scale system development. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or working in cutting-edge AI research environments.

What is a Deep Learning Engineer job?

A Deep Learning Engineer is a specialized software engineer who designs, develops, and optimizes deep learning models. They work with neural networks, large datasets, and frameworks like TensorFlow or PyTorch to build AI systems for tasks like image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, performance tuning, and deploying models into production. Strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration are essential for this role.

What are the key skills and qualifications needed to thrive in the Deep Learning Engineer position, and why are they important?

To thrive as a Deep Learning Engineer, you need a strong background in mathematics, machine learning theory, and programming (especially Python), often supported by a relevant degree in computer science, engineering, or related fields. Proficiency with frameworks such as TensorFlow, PyTorch, Keras, as well as experience with GPUs and cloud platforms, is highly valued, and certifications in AI or deep learning can further enhance your profile. Effective problem-solving, strong collaboration skills, and clear communication are important soft skills for excelling in interdisciplinary teams. These abilities ensure that you can develop robust deep learning models, adapt to evolving technologies, and contribute value in both technical and collaborative settings.

What engineers make $500,000?

Senior engineers in high-demand fields such as software, data science, and machine learning can earn $500,000 or more annually, especially with extensive experience, specialized skills, and leadership roles. Roles like senior software engineers, machine learning engineers, and data architects at large tech companies or startups often reach this compensation level through base salary, bonuses, and stock options.

What do deep learning engineers do?

Deep learning engineers develop and implement neural network models to solve complex problems such as image recognition, natural language processing, and speech analysis. They work with large datasets, use frameworks like TensorFlow or PyTorch, and often require knowledge of programming, mathematics, and machine learning principles.

What are the typical daily tasks and responsibilities of a Deep Learning Engineer?

Deep Learning Engineers typically spend their days designing, developing, and optimizing neural network models for tasks like image recognition, natural language processing, or recommendation systems. They preprocess and analyze large datasets, experiment with model architectures, and tune hyperparameters to achieve the best performance. Collaboration is often required with data scientists, product managers, and software engineers to integrate models into real-world applications and scale solutions for production. Additionally, many deep learning engineers review current research, stay updated on advancements in AI, and continuously improve their skills. This role offers a dynamic work environment where learning and innovation are highly encouraged.

What engineers make $300,000 a year?

Senior deep learning engineers and AI specialists with extensive experience, advanced skills in machine learning frameworks, and strong domain knowledge can earn $300,000 or more annually. These roles often require advanced degrees, certifications, and work in high-demand industries such as technology, finance, or healthcare, typically involving leadership responsibilities and complex project management.
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Deep Learning Engineer jobs near you
Senior Deep Learning Framework Communications Engineer

Senior Deep Learning Framework Communications Engineer

NVIDIA

Westford, MA • On-site

Full-time

Re-posted 16 days ago

Job description

Job Summary:
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks and improve AI compilers for large-scale workloads.
Responsibilities:
• Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production
• Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models.
• Improve AI compilers to hide communications or perform automatic fusion.
• Conduct in-depth AI workload performance characterization on multi-GPU clusters.
• Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads.
• Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms.
• Influence the roadmap of communication libraries - NCCL & NVSHMEM.
• Collaborate with a very dynamic team across multiple time zones.
Qualifications:
Required:
• B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 5+ software engineering and HPC/AI experience
• Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang
• Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe)
• Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile)
• Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems)
• Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc)
• Adaptability and passion to learn new areas and tools
• Flexibility to work and communicate effectively across different teams and timezones
Preferred:
• Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals)
• Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes
• Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.
Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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