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Deep Learning Developer Jobs in Michigan (NOW HIRING)

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

New

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

New

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

New

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

New

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

New

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

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Deep Learning Developer information

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 Developer or AI research lead, often involving advanced skills in machine learning frameworks, data modeling, and programming. Such roles usually require extensive experience, specialized knowledge, and may include responsibilities like developing innovative AI solutions or leading AI teams in tech companies or research institutions.

What are the key skills and qualifications needed to thrive as a Deep Learning Developer, and why are they important?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What are Deep Learning Developers?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

Which 3 jobs will survive AI?

Deep Learning Developers are likely to continue to be in demand as AI advances because they design and improve AI models, requiring specialized skills in programming, mathematics, and data analysis. Other roles expected to persist include AI ethics specialists and AI system trainers, as human oversight and ethical considerations remain essential. These jobs involve complex problem-solving and domain expertise that are difficult to fully automate.

What is the difference between Deep Learning Developer vs Machine Learning Engineer?

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges Deep Learning Developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.

What engineer makes $500,000 a year?

Highly experienced deep learning developers or AI engineers with specialized skills in neural networks, large-scale data processing, and advanced machine learning frameworks can earn $500,000 or more annually, especially in senior or leadership roles at major tech companies or startups. Such roles often require advanced degrees, extensive experience, and a strong track record of deploying impactful AI solutions.

What engineers make $300,000 a year?

Deep learning developers and AI engineers with extensive experience, advanced skills in machine learning frameworks, and strong domain expertise can earn $300,000 or more annually, especially in high-demand industries or senior roles. Compensation often includes base salary, bonuses, and stock options, particularly at leading tech companies or startups with significant funding.
What cities in Michigan are hiring for Deep Learning Developer jobs? Cities in Michigan with the most Deep Learning Developer job openings:
Infographic showing various Deep Learning Developer job openings in Michigan as of July 2026, with employment types broken down into 74% Full Time, 23% Part Time, and 3% Contract. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution.

Machine Learning Engineer

Bespoke Labs

Warren, MI • On-site

Full-time

Posted yesterday


Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination