Deep Learning Field Engineer Jobs

Collaborate with software and computer groups to design and implement data management, model training and inference flows.

Bring forward creative ideas, develop proof-of-concepts, integrate algorithms into production code, and work with other team members in global project teams.

Apply to this posting for Future Opportunities with KLA.

Academic background required in any one of the following areas:

Familiarity with any one of the following is a plus:

Full range of benefits - 100% covered medical/ dental/ vision

What we can offer a Director of Deep Learning Research:

Will compensate for relocation (with stipend upon offer) as we are a fully on-site team!

Make a profound impact at a high-growth tech software company

Competitive base salary and annual bonus

15 days annual PTO plus holidays

B.S. degree or higher in computer science (or similar) or equivalent experience

Strong programming skills in C/C++ development and familiarity with Python.

Excellent problem solving skills, including applications of algorithms and data structures.

Experience with performance analysis, profiling, and code optimization.

Practical experience with machine learning, especially deep learning.

Experience with computer architecture and building performance models for CPUs, GPUs, or other accelerators.

MS or PhD degree in computer science, computer architecture, electrical engineering or related field or equivalent experience.

Experience with deep learning workloads, including performance tuning considerations such as parallelization and fusion strategies;

Experience with core deep learning kernels such as matrix multiply and convolution

Experience with GPU computing (CUDA)

Experience with deep learning frameworks like PyTorch

Programming fluency with C++ and ideally Python

Remote - Must already be US-based

Highly competitive salary, leading equity package, and benefits.

- +3 yrs experience after PhD (industry or post-doctoral research)

large-scale causal inference, deep learning, generative AI, and reinforcement learning

- Have worked in the system biology, omics or single cell field

You can apply below or contact Jack Cartlidge at Cubiq Recruitment for more information.

We prefer that you possess some computer programming experience and/or extensive experience documenting APIs in the code.

Experience with Sphinx, using reStructuredText and/or Markdown, would help set you apart.

Some experience with DITA (ideally using Oxygen XML Editor) would also be helpful.

Skills for supporting multiple projects and multi-tasking.

BA/BS in Technical Communications, Computer Science, Engineering, or related field (or equivalent experience).

Experience with Acrolinx, Grammarly, or similar tools.

Must have hands on experience with software development and process specifically for system software development.

Experience influencing decisions and leading teams in a matrix environment.

It is important to have excellent communications and technical presentation skills.

BS, EE or CS or equivalent experience with 7+ years of experience.

Previous experience with productizing enterprise server systems including experience of - coordinating activities between HW / SW organizations is highly desirable.

Experience with productivity tools and process automation is big plus.

Strong knowledge of C/C++, python and firsthand experience with parallel programming, ideally CUDA C/C++.

A Bachelors or Masters Degree in an engineering or computer science related field or equivalent experience

8+ years of relevant work experience. 5+ years in Machine Learning frameworks such as PyTorch, Tensorflow, ONNX Runtime, and TensorRT

Study and work on ground breaking Generative AI models. Ensure the best possible performance on current- and next-generation GPU architectures.

Architect, design and use your coding expertise to optimize, deploy and productize AI models. Write effective, maintainable, and well-tested code

Collaborate closely with the architecture, research, libraries and tools teams at NVIDIA to achieve ideal results for AI problems at hand

Pre training of large GPU clusters

Optimize Inference throughput of custom neural net architectures

Develop, test and optimize algorithms for new neural net architectures

Scrap and compile internet-scale data

Work with world class Engineers

Send a copy of your resume along with your availability in PST hours to [email protected]

Strong Mathematical fundamentals and algorithms skills or experience.

Project management tools (e.g. JIRA, Git, Microsoft Project).

PhD or Masters or equivalent experience.

Experience in Computer Science, Artificial Intelligence, Applied Math.

Excellent programming, debugging, performance analysis, and test design skills.

Ability to work independently and manage individuals’ R&D efforts.

Experience in financial engineering and quantitative modeling, including formulating trading strategies

Graduate degree in computer science, data science, AI/ML, mathematics/statistics, engineering, or an equivalent technical field

Excelled in a fast-paced startup environment

Profit sharing (estimated minimum value of $25,000/year; maximum is uncapped)

But this position will likely be part of our first physical office (in the San Francisco Bay Area)

Non-Bay Area candidates are welcomed to apply if they plan to relocate to the San Francisco Bay Area

Need minimum of 1 year work experience in data science or related field.

Aid in implementing skills of a Data Scientist Level 1.

Knowledge of Python and basic understanding of DL tools.

Excellent communication and writing skills.

Preference for last semester international students.

Support the Deep Learning team with tasks related to DL tools and transformer-based models.

BS, MS, PhD or equivalent experience in Computer Science, Computer Engineering

Excellent communication skills, and an interest in collaboration and teamwork

Experience in working with TensorRT, PyTorch, TensorFlow, ONNX Runtime or other ML frameworks

Experience in GPU kernel programming using CUDA or OpenCL.

Develop components of TensorRT, NVIDIA’s SDK for high-performance deep learning inference.

Use C++ and Python to build graph parsers, optimizers, and tools for effective deployment of trained deep learning models.

Formal training in Deep Learning and experience with one or more of the following: Graph Neural Networks, Diffusion Models. Transformers

Develop Deep Learning approaches to solving long-standing problems in Biology

Train cutting-edge Neural Networks on complex biological data

Develop highly sophisticated models to reduce the time/cost related to therapeutics development

Ph.D. in Computer Science, Machine Learning, Mathematics, Data Science, Statistics, Physics, or a related field.

Strong background in Mathematics (Linear Algebra, Calculus, Statistics, and Probability Theory)

Demonstrated strong C++ programming and software design skills, including debugging, problem solving, performance analysis, and test design

Experience with performance-oriented parallel programming, even if it’s not on GPUs (e.g. with OpenMP or pthreads)

Or experience in SCM (e.g. Git, Perforce) and build systems (e.g. Make, CMake, Bazel)

Experience in optimizing/tuning BLAS or deep learning library kernel code

Experience with code coverage and static code analysis tools

Writing highly tuned compute kernels, mostly in C++ CUDA, to perform core deep learning operations (e.g. matrix multiplies, convolutions, normalizations)

Strong Mathematical fundamentals and algorithms skills or experience.

Excellent analytical, programming, debugging, performance analysis, and test design skills.

Experience doing performance analysis and tuning.

Excellent C/C++, GPU programming (CUDA or OpenCL) skills.

Develop algorithms for deep learning, data analytics, machine learning, or scientific computing.

Construct and curate large problem specific datasets.

Masters or PhD in Computational Linguistics (or equivalent field with computational emphasis) or equivalent experience

Knowledge of scripting languages (e.g. Python, bash)

Knowledge of grammar, language structure, phonetics/phonology, and ability to analyze/validate phonetic transcriptions

Experience with building and customizing large language models, speech recognition, and speech synthesis models

Excellent written and spoken communication skills

Experience with MLOps workflows & traceability and versioning of datasets and understanding of MLOps life cycle

Experience with self-supervised and auto-regressive natural language processing models such as BERT and GPT2

Strong written and oral communication skills

Translate drug discovery challenges into ML problems

Maximize value of public and proprietary data assets

Develop and prototype novel ML algorithms for impactful drug discovery problems

Train and validate large deep learning models at scale

Deep learning and machine learning technologies and functions for knowledge creation, deployment and applications

Working experience in machine learning and deep learning

Strong knowledge of C++/C# programming and/or python scripting

2D/3D image analysis and computer vision technologies and functions

2D/3D pattern tracking and kinetic analysis technologies and functions

Speed up and improve existing core technology algorithms and functions for optimal deployment

At least 3 years hands-on experience with deep-learning research and application.

At least 3 years programming experience (Python/C++ or any high-level language).

Research, development, and integration of vision-based road perception algorithms.

Overseeing and developing complex data pipelines, from data collection, to annotation, and generation.

Integration with C++ - based Autonomous Vehicle software.

Testing and finetuning developed algorithms/models in Imagry’s Autonomous Vehicle in Haifa.