דרושים » תוכנה » Senior Deep Learning Researcher, Diffusion

Requirements:
* A Masters or Ph.D. in Computer Science, Engineering, Mathematics, or a related field.
* 5+ years of industry experience in developing and productizing computer vision and deep learning algorithms.
* 3+ years of experience working on major AI vision problems in detection, classification, and segmentation with a proven track record of successfully leading algorithm teams
* Hands-on research and industry experience with a proven track record
* Experience in managing different algorithm team members such as ML & CV developers
* Experience with Major Deep Learning Frameworks (such as PyTorch, TensorFlow, etc.).
* Experience in the fields of: Semi-supervised learning/ Unsupervised learning/ Active learning/ Reinforcement learning/ Radiance fields/ Tracking / Identification / Image Retrieval / Anomaly Detection / Pose Estimation / OCR - Advantage
Attributes:
* Comfortable in unexplored territory.
* Possess the skill to break down intricate problems into manageable parts, followed by proposing effective and actionable solutions.
* Maintain a steadfast focus on delivering not just insights but actionable results that have a measurable impact on the project or the organization
* Good communication skills with a can-do attitude.
* Agility and multitasking, Independent and self-motivated.
* Good time management, task prioritization skills, and accountability.
* Excellent English.
 
Why us: Pioneer Advanced Solutions: Harness cutting-edge technologies in AI, Machine Learning, and computer vision to revolutionize vehicle inspections. Drive Global Impact: Your innovations will play a crucial role in enhancing automotive safety and reliability, impacting lives and businesses on an international scale. Career Growth Opportunities: Participate in a journey of rapid development, surrounded by groundbreaking advancements and strategic industry partnerships.

Requirements:
B.Sc./M.Sc. in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
5+ years of experience in VLSI CAD tool development, with a strong focus on integrating AI/ML techniques into EDA workflows.
Proficiency in Python and at least one AI/ML framework (such as TensorFlow, PyTorch, or scikit-learn).
Hands-on experience with VLSI physical design and familiarity with industry-standard EDA tools (e.g., Synopsys, Cadence).
Knowledge of data preprocessing, feature engineering, and model deployment as applied to VLSI design challenges.
Experience developing and maintaining automation scripts (Python, Perl, Tcl, Make).
Strong analytical skills in evaluating the impact of AI solutions on design quality, performance, and productivity.
Excellent communication skills and the ability to work cross-functionally in a fast-paced environment.
Self-motivation, attention to detail, and a track record of delivering robust solutions to production.
Ways to stand out from the crowd:
Demonstrated experience deploying AI/ML models in production VLSI CAD environments.
Contributions to open-source AI/EDA projects or publications in relevant conferences/journals.
Deep understanding of VLSI design challenges-such as timing closure, power optimization, or yield enhancement-and how AI can address them.
Experience with cloud-based or distributed compute environments for large-scale AI training and inference.
Strong ownership, curiosity, and a passion for continuous learning and innovation.

Requirements:
5+ years of experience in Deep Learning
2+ years of experience leading a team of DL researchers
Strong technical skills in ML, including deep learning (bonus: recommendation systems)
Excellent communication and interpersonal skills
Ability to work independently and as part of a team
Master's degree in Computer Science, Mathematics, Physics, Engineering, Statistics, or a related field

Requirements:
B.Sc. or higher in Electrical Engineering or related field: Solid educational foundation in electrical engineering principles, particularly in power integrity and physical design.
3+ years of experience in power integrity engineering: Proven experience in power integrity analysis, mitigation, and optimization, especially in the context of high-performance computing or networking hardware.
Proficiency with industry-standard PI tools: Hands-on experience with tools such as Cadence, Ansys, or other EM simulation tools, including power delivery network (PDN) analysis and design.
Ability to collaborate across teams: Strong communication and teamwork skills, with a track record of working closely with hardware and design teams to implement power delivery strategies.
Adaptability and problem-solving skills: Ability to thrive in a dynamic, fast-paced environment where quick thinking and creative solutions are often required.
Ways to stand out from the crowd:
Advanced degree (M.Sc./Ph.D.) in Electrical Engineering: Specialization in power integrity, signal integrity, or related fields, with a focus on cutting-edge research or projects.
Programming skills: Proficiency in Python, tcl, or other relevant programming languages for automating analysis or enhancing tool capabilities.
Innovative mindset: A demonstrated ability to push the boundaries of whats possible in power integrity design, contributing to our companys legacy of continuous innovation.

Requirements:
Advanced degree (M.Sc. or higher) in a relevant field (Computer Science, EE, Physics, etc.).
5+ years of experience in the industry.
Experience with DL, ML, and numerical libraries like: PyTorch, Tensorflow, NumPy, Pandas.
Solid Python programming skills.
Proven track record in solving novel DL challenges.
Algorithmic and Deep learning design skills.
Ability to learn and adapt quickly.
Strong Data analysis and presentation skills.
Excellent communication and teamwork skills.

Requirements:
* 4+ years of industry experience in the development and productization of Deep Learning Algorithms.
* Hands-on industry experience working on major Vision problems in the fields of Detection, Classifications, and Segmentation.
* Experience with Python - Must, C / C ++ - An advantage.
* Experience with Major Deep Learning Frameworks (such as PyTorch, TensorFlow, etc.).
* Experience working with Tracking / Identification / Image Retrieval / Anomaly Detection / Pose Estimation / OCR/Image Registration -An advantage.
* Comfortable in unexplored territory, independent and self-motivated.
* Relevant Degree.
* Excellent English.
 
Why us: Pioneer Advanced Solutions: Harness cutting-edge technologies in AI, Machine Learning, and computer vision to revolutionize vehicle inspections. Drive Global Impact: Your innovations will play a crucial role in enhancing automotive safety and reliability, impacting lives and businesses on an international scale. Career Growth Opportunities: Participate in a journey of rapid development, surrounded by groundbreaking advancements and strategic industry partnerships.

Requirements:
5+ years experience as a Data Scientist
2+ years experience working with Deep Learning.
Experience working with recommender systems - an advantage
Hands-on experience building and deploying deep learning models to production
High level scripting and programming skills in Python
Superior verbal, visual, and written communication skills to educate and work with cross functional teams on controlled experiments.
Team player, responsible, delivery-oriented
Troubleshooter, problem-solver who knows how to navigate trade-offs
Work experience as a data analyst - an advantage
At least a Master's degree in Computer Science, Math, Physics, Engineering, Statistics or other technical field.
Experience in ML over user personalization, ad-tech, or highly imbalanced data- an advantage.

Requirements:
Masters/Ph.D. in Computer Science, Electrical Engineering, Machine Learning, information systems engineering, or related field.
5+ years of hands-on experience with developing & maintaining production class Machine Learning projects aimed towards solving business problems.
High proficiency in Python
Hands-on proficiency with modern generative AI models, prompt engineering, multi-agents, and RAG architectures. Also, a solid understanding of transformers, optimized fine-tuning techniques, and evaluation methodologies of LLMs while using relevant frameworks (Hugging Face, LangChain, LlamaIndex, etc)
Familiarity with embedding models and vector databases - advantage
Experience in data exploration and visualization.

Requirements:
B.sc or M.sc in Engineering, Mathematics, Physics, or Computer Science or equivalent experience
5+ years of experience in software development or extensive data analytics, CUDA experience highly desirable.
Experience working with modern Deep Learning software architecture and frameworks including PyTorch, VLLM, Triton
Proven Exposure to GPU technology and CUDA programming
Demonstrable experience in strategy, research, communications.
Capable of working in a constantly evolving environment without losing focus.
Committed with strong analytical and problem solving skills.
Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects.
Direct experience participating in communities (expertly or as highly engaged developer).
Ways To Stand Out From The Crowd:
Technical knowledge of developer digital platforms and their trends.
Experienced working with containers, Kubernetes and MLoPS tools
Exposure to C, C++ and Python.
Research background.
Good presentation skills.

Requirements:
MSc or PhD in Electrical Engineering, Computer Science, or Computer Engineering or equivalent experience.
At least 5 years of experience.
Background in data center network protocols, threat modeling, and network security, as well as common mitigation techniques.
Programming and debugging fundamentals across languages such as Python, and C/C++.
Strong communication skills and a genuine passion for working together as a team are vital.
Ways to stand out from the crowd:
Proven security research experience and publications in top security conferences.
Experience with high-scale deployment challenges, RDMA networking, and machine learning.
Architectural background in hardware and software systems codesign.