לוח משרות דרושים Deep learning researcher משרה מלאה

Requirements:
Required Qualifications:
Proven track-record in single cell genomics is a must
MSc or Ph.D. in computer science, bioengineering, computational biology, or related discipline - MSc + 5 years of relevant industry experience or PhD with 0-4 years of relevant industry experience, specifically hands-on deep learning experience
Demonstrated experience leading projects using custom deep learning models to solve biological problems
Strong technical abilities in Python and ML libraries (PyTorch, sklearn, an advantage: DeepSpeed/Zero or similar)
Evidence of engagement with open source projects and community
Excellent written and verbal communication skills
Desired personal traits:
You want to make an impact on humankind
You prioritize We over I
You enjoy getting things done and striving for excellence
You collaborate effectively with people of diverse backgrounds and cultures
You have a growth mindset
You are candid, authentic, and transparent.

Requirements:
2+ years of experience working with large-scale Pytorch-based deep learning applications on GPUs and TPUs using CUDA in multi-node multi-GPU scenarios
2+ years of experience building, training and fine-tuning pipelines for large language models (LLMs) using distributed training approaches for both model and data
2+ years of experience building serving APIs for sub-second latency inference of large language models using various optimization techniques
Extensive experience with Pytroch, DeepSpeed, Megatron-LM, and the Huggingface ecosystem
Proven track record in fine-tuning embedding models, and re-rankers.
1+ years of experience with model training optimization and distributed training, using libraries such as HF Accelerate, BitsandBytes, and Flash-Attention to enhance training efficiency and scalability.
Experience in managing machine learning experiments and monitoring model performance, using tools like Weights and Biases and MLFlow.
Familiarity with embedding models inference libraries (e.g.,Infinity, Text Embedding Interface) and LLM inference libraries (e.g., VLLM, Text Generation Interface).
Experience with Keras, JAX/FLAX an advantage
Experience with advanced finetuning methods such as RLHF, DPO, KTO, ORPO, etc.. an advantage
Experience with parameter efficient finetuning methods such as LoRA, DoRA, ReFT, IA3, etc.. an advantage.

Requirements:
5+ years of professional experience as s Computer Vision researcher.
MS.C. or PHd in EE / CS - an advantage
Experience with Python or Matlab- an advantage
Knowledge of working with Deep Learning - an advantage
Effective written and verbal English to communicate with our international team.
Solid analytical and problem-solving skills paired with the ability to develop creative and efficient solutions.

Requirements:
* Master's degree in Computer Science, Statistics, Mathematics, or related field, or equivalent professional experience.
* At least 5 years of experience in Deep learning AI, with a strong foundation in research.
* Minimum of 3 years of leadership experience of ML/ data Science team.
* Proficiency in data structures, data modeling.
* Extensive knowledge of mathematics, statistics, probability theory, and algorithms.
* Exceptional leadership skills, with a track record of developing high-performing teams.
* Strong communication skills, able to effectively convey complex AI concepts to a variety of audiences.

Requirements:
* A Master’s 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 UVeye: 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. in relevant field.
At least 5 years experience as a researcher
In depth familiarity with deep-learning algorithms, classic machine learning and computer vision.
Experience in Python & PyTorch
Good communication skills, self-motivated, proactive, flexible and passionate about learning
Focus on delivery of solutions for real world scenario in challenging timeframe.
Deep knowledge in CNN for object detection, classification & segmentation
ADVANTAGES
Familiar with Electro optics devices (Thermal cameras, lenses, etc.)
Experience working in multidisciplinary environments
Experience in the automotive industry.

Requirements:
Requirements
1.Project Management- Experience in managing AI projects, including resource and timeline coordination.
2.Team Leadership:- Proven track record of leading AI teams and developing technological infrastructures for AI solutions.
3.Strategic Development: - Ability to develop and implement organizational AI strategies successfully.
4.Technical Expertise:- Deep understanding of AI algorithms, techniques, and BI tools.
5.AI Solutions Knowledge:** Broad knowledge of AI solutions spectrum (e.g., Machine Linux, deep learning, GEN AI) and when to apply different capabilities.