Generative Ai Engineer

Generative Ai Engineer Developer Jobs

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Today

Evaluation & Insights Machine Learning Engineer

Apple Cupertino, CA

Cupertino, CA

Today

$185k - $325k/yr Full time Ai Evaluation Ai Testing And Evaluation Artificial Intelligence

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Job Description

Work on Apple’s Human-Centered AI team to evaluate and improve AI systems using data science, model behavior analysis, and qualitative insights.

Architect and execute comprehensive evaluation suites for LLMs and multimodal models, surfacing edge cases in multi-step reasoning, factuality, adversarial robustness, safety, and alignment
Build deterministic, heuristic, and LLM-assisted evaluation frameworks (including LLM-as-a-judge and reward modeling) to quantify human-perceived quality metrics such as helpfulness and hallucination rates
Convert qualitative failure modes into quantifiable loss patterns, programmatic guardrails, and actionable data-mixture adjustments for both training and inference
Partner with engineering teams to refine model behavior using evaluation telemetry to guide prompt engineering, Retrieval-Augmented Generation (RAG) strategies, and model fine-tuning
Apply advanced ML techniques (embedding-based clustering, representation learning, perturbation analysis) to map error taxonomies and latent failure manifolds
Develop robust MLOps workflows to codify evaluation metrics, automate regression testing across model checkpoints, and integrate human-centric assessments into ML CI/CD pipelines
Design scalable, distributed inference and processing pipelines (for example, Ray and vLLM) to support high-throughput evaluation, automated annotation, and large-scale output analysis
Define quantitative evaluation frameworks capturing nuanced human factors such as trust calibration, conversational state tracking, and interpretability
Build automated evaluation pipelines that use LLMs to assess outputs at scale, with optimization for high correlation to human baseline annotations
Collaborate across Apple with ML researchers, software developers, and product managers to translate product requirements into reliable and efficient evaluation infrastructure

Requirements

Knowledge of human factors, HCI, or cognitive science methodologies as applied to AI system design
Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Cognitive Science, or a related technical field
8+ years of relevant industry experience in ML Engineering or Applied Research
Advanced proficiency in Python and modern deep learning ecosystems (PyTorch, JAX, Hugging Face)
Proven experience building scalable ML inference pipelines, model-evaluation workflows, and structured rating frameworks for large-scale AI systems
Strong ability to interpret unstructured model outputs (text, transcripts, embedding spaces) and synthesize qualitative findings into actionable engineering guidance and training objectives
Hands-on experience developing, fine-tuning, or evaluating LLMs, multimodal models, and NLP systems
Deep familiarity with AI quality metrics, hallucination detection techniques (for example SelfCheckGPT), model alignment (RLHF/DPO), and LLM-as-a-judge frameworks (for example G-Eval and DeepEval)
Experience building internal tools or automated pipelines for ML workflows using tools like MLflow and Weights & Biases or similar platforms
Strong familiarity with advanced prompt engineering, RAG architectures (vector databases, semantic search), and Fine-Tuning

Technologies

Python
PyTorch
JAX
Hugging Face
LLM-as-a-judge
reward modeling
Retrieval-Augmented Generation (RAG)
embedding-based clustering
representation learning
perturbation analysis
MLOps
CI/CD pipelines
Ray
vLLM
trust calibration
SelfCheckGPT
RLHF
DPO
G-Eval
DeepEval
MLflow
Weights & Biases
vector databases
semantic search
Fine-Tuning
LLM-assisted evaluation frameworks

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Discounted products and free services
Reimbursement for certain educational expenses, including tuition
Discretionary restricted stock unit awards
Opportunity to purchase Apple stock at a discount via the Employee Stock Purchase Plan
Base pay range between $184,700 and $324,800
Comprehensive total compensation package may include discretionary bonuses or commission payments as well as relocation

Pay & Benefits

Base pay range: $184,700 to $324,800 (depends on skills, qualifications, experience, and location)
Employee stock programs: eligibility-dependent discretionary employee stock programs and Employee Stock Purchase Plan participation
Benefits include comprehensive medical and dental coverage, retirement benefits, discounted products and free services, and tuition reimbursement for formal education related to career advancement
This role might be eligible for discretionary bonuses or commission payments and relocation
Note: Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program

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1d ago

Machine Learning Engineer

Apple Cupertino, CA

Cupertino, CA

1d ago

$216k - $325k/yr Full time Artificial Intelligence Autoregressive Models Deep Learning

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Job Description

Design and build next-generation generative AI models that support Apple Intelligence and power experiences like Genmoji, Image Playground, and Image Wand.

Responsibilities

Develop modern generative model technology using diffusion and auto-regressive approaches
Apply the latest AI research quickly and effectively to deliver impactful improvements
Pioneer proprietary, experimental ideas tailored to Apple’s ecosystem
Advance state-of-the-art modeling through work spanning large-scale training and on-device optimizations

Requirements

M.S. or PhD in Computer Science (or related field such as Electrical Engineering, Robotics, Statistics, Applied Mathematics) or equivalent experience
2+ years experience training and fine-tuning modern image/video generation models
Experience in an academic or industrial research environment
Proficiency with an ML framework such as PyTorch, TensorFlow, or JAX
Strong communication skills, including the ability to drive clarity in ambiguous situations

Technologies

PyTorch
TensorFlow
JAX

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Discounted products and free services
Reimbursement for certain educational expenses, including tuition for formal education related to advancing your career
Opportunity to become an Apple shareholder via Apple’s discretionary employee stock programs
Discretionary restricted stock unit awards
Ability to purchase Apple stock at a discount through optional participation in the Employee Stock Purchase Plan
Discretionary bonuses or commission payments and relocation (discretionary)

Preferred Qualifications

Demonstrated strong industrial research, including delivery of complex projects or publications in top-tier venues

Location: Cupertino, CA (onsite)

Salary: USD 216,200 - 324,800 per year

Minimum experience: 2 years

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1d ago

Machine Learning Engineer

Johns Hopkins Applied Physics Laboratory (APL) Laurel, MD

Laurel, MD

1d ago

$100k - $245k/yr Full time Ai Engineer Ai Ml Artificial Intelligence

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Job Description

The Machine Learning Engineer role at Johns Hopkins Applied Physics Laboratory (APL) supports the full lifecycle of machine learning algorithm development, from design through evaluation and implementation. The work is focused on national defense non-kinetic systems and the development of advanced AI methods and software pipelines for real-world planning and decision-making.

Location

Laurel, MD (onsite)

Salary

USD 100,000 - 245,000 per yearly

Role Summary

As a Machine Learning Engineer, you will design, implement, and evaluate ML algorithms for challenging problems in planning, perception, coordination, and control. The position includes building and integrating intelligent decision-making capabilities, leveraging cutting-edge AI approaches and development pipelines.

Responsibilities

Design, implement, and evaluate advanced machine learning algorithms to address challenging real-world planning, perception, coordination, and control problems for national defense.
Develop software pipelines that connect data streams, simulation environments, and intelligent decision-making algorithms.
Apply technologies and concepts at the forefront of AI, including deep reinforcement learning, foundation models, large language models, convolutional/recurrent/graph neural networks, computer vision, and physics-based modeling and simulation tools.
Collaborate with scientists and engineers within the group and with partner teams across APL.
Engage directly with sponsors to communicate proposed concepts, solutions, and analysis.

Requirements

Have a Bachelor’s degree in Mathematics, Physics, Engineering, Computer Science, or a related field.
Have at least 2+ years of experience in machine learning and data science fields.
Have at least one year of hands-on experience applying or developing machine learning algorithms using common libraries such as PyTorch or TensorFlow.
Have strong foundational knowledge in at least two of the following: classification, clustering, deep learning, reinforcement learning, computer vision (object detection and visual tracking), multi-agent systems, or optimization/control theory.
Demonstrated experience working with version control software such as Git.
Strong communication skills, both verbal and written.
Be able to obtain an Interim Secret security clearance by your start date and ultimately obtain a Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet requirements for access to classified information, including U.S. citizenship.

Technologies

PyTorch
TensorFlow
Git
Deep reinforcement learning
Foundation models
Large language models
Convolutional neural networks
Recurrent neural networks
Graph neural networks
Computer vision
Physics-based modeling and simulation tools

Preferred Qualifications

You will go above and beyond minimum requirements if you have one or more of the following:

An MS in Mathematics, Physics, Engineering, Computer Science, or a related field.
5+ years of experience designing and implementing AI/ML algorithms for a variety of datasets.
Proven experience applying state-of-the-art deep learning techniques to solve distributed resource allocation problems.
Hands-on experience building computer vision pipelines for detection, tracking, segmentation, or multi-modal sensor fusion.
Experience with modeling and simulation platforms such as AFSIM, Blender, Unity, or Unreal.
Comfort working in high performance computing environments (GPU/CPU clusters).
Proficiency in one or more technology areas including multi-agent reinforcement learning, geometric deep learning, multi-modal sensor fusion, or agentic AI.
A track record of writing deployable, production-level code in Python and/or C/C++ for real-world applications.

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2d ago

Data Scientist / Machine Learning Engineer

CorTech Auburn Hills, MI

Auburn Hills, MI

2d ago

Full time Artificial Intelligence Automation Cloud

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Job Description

CorTech is seeking a Data Scientist / Machine Learning Engineer to design, develop, and deploy AI and deep learning solutions for the automotive industry. The role focuses on practical model delivery across computer vision, predictive maintenance, anomaly detection, and generative AI initiatives, with close collaboration across teams.

Role Responsibilities

Design, develop, and deploy AI models, including computer vision and generative AI, to address complex automotive challenges.
Partner with cross-functional teams to understand business needs and identify where machine learning can create measurable value.
Use generative AI models to support innovation in design, R&D, and manufacturing processes.
Optimize existing machine learning models for performance and scalability, leveraging CUDA advanced GPU architectures and parallel computing frameworks.
Design and implement end-to-end machine learning pipelines for data preprocessing, model training, and performance evaluation.
Implement machine learning solutions using Python and deep learning frameworks including PyTorch and TensorFlow.
Apply statistical techniques and machine learning algorithms to solve domain-specific problems in the automotive sector.
Track advances in data science, machine learning, deep learning, and AI, and apply new techniques to support continuous innovation.
Develop and maintain documentation for data analysis methods, model development, and deployment processes to support reproducibility and compliance with industry standards.

Required Qualifications

PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
Proven experience in machine learning, deep learning, and AI.
Strong command of Python, CUDA, and GPU architectures for parallel computing and model optimization.
Solid knowledge of machine learning architectures and techniques, with emphasis on computer vision and generative AI.
Proficiency with deep learning frameworks such as PyTorch and TensorFlow.
Experience with parallel computing and optimization for high-performance computing environments.
Ability to work collaboratively and communicate complex ideas clearly to non-technical stakeholders.
Innovative mindset and strong interest in solving challenging problems and advancing technical capabilities.
Strong analytical skills, including interpreting complex data and turning results into strategic insights and practical solutions.
Minimum 5 years of experience in a machine learning engineering role, preferably in automotive or a related sector.
Demonstrated experience building and deploying machine learning models for real-world applications.
Self-directed approach with interest in ongoing learning and professional development.
Experience with Agile and a cloud provider such as Azure would be a plus.

Education

PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

Location

Auburn Hills, MI (onsite)

Minimum Experience

5 years

Technologies

Python
CUDA
PyTorch
TensorFlow
CUDA advanced GPU architectures
Parallel computing frameworks
Agile
Azure

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Generative Ai Engineer Developer Jobs

Evaluation & Insights Machine Learning Engineer

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