דרושים » תוכנה » Applied AI Engineer

We are looking for a talented AI Solutions Engineer to join our innovative AI team. In this role, you will act as a bridge between our AI capabilities and internal customers, helping teams effectively adopt and integrate cutting-edge AI based solutions. Our team develops advanced AI applications including agentic workflows, Retrieval-Augmented Generation (RAG) systems, Large Language Model (LLM) based solutions, AI agents, MCPs, and more. You will play a key role in ensuring these technologies deliver real value by working closely with users and contributing hands-on development. We are looking for a motivated teammate who enjoys working with technology, people and developing new capabilities.


What you'll be doing:

Lead technical engagements to showcase AI capabilities and demonstrate best practices.

Support integration of AI solutions into existing systems and workflows.

Guide users on how to effectively use AI tools and platforms to maximize impact.

Develop and customize AI solutions (e.g., RAG pipelines, LLM-based applications, evaluation, agents, etc.) based on customer use cases while ensuing high reliability.

Troubleshoot technical issues and provide hands-on support during onboarding and adoption.

We are looking for an experienced, independent team player who has great data & computer science skills, a passion for data, and excellent analytical and algorithmic skills.

This role is diverse, encompassing AI/ML, data analysis, and backend engineering.

You will play a crucial role within a mission-critical team responsible for managing the heart and brain of Sunbits primary products. This involves working on core systems, such as POS underwriting models, models for merchant operations, Fraud investigator AI agents and more.

You will participate in cutting-edge risk management systems that safeguard the loan product's financial operation, as well as operational systems, with a direct impact on its financial success.

Our AI/ML team is part of the R&D group, so you will work closely with engineers and product managers as well.

Key Responsibilities
Research and develop statistical behaviors, study domain-specific data.
Develop state-of-the-art machine learning models end to end, including development, deployment, and continuous improvement. Both in-weight learning and in-context learning, for risk / fraud / operations related projects. This includes integrating models into production services and ensuring compliance with regulatory processes (e.g. providing evidence for production model audits).
Operate backend infrastructure for training and deploying ML models, ensuring optimal performance and reliability.
Develop and maintain Python code for translating ML model outputs into financial decisions.
Analyze 15+ different data sources in order to train models and agents to catch fraudulent patterns.
Conduct analytical research on our models impact on the portfolio.
Strategize and implement changes to enhance portfolio performance.

Join our companys AI research group, a cross-functional team of ML engineers, researchers and security experts building the next generation of AI-powered security capabilities. Our mission is to leverage large language models to understand code, configuration, and human language at scale, and to turn this understanding into security AI capabilities which will drive our company AI future security solutions.
We foster a hands-on, research-driven culture where youll work with large-scale data, modern ML infrastructure, and a global product footprint that impacts over 100,000 organizations worldwide.
Key Responsibilities
Your Impact & Responsibilities
As a Senior ML Research Engineer, you will be responsible for the end-to-end lifecycle of large language models: from data definition and curation, through training and evaluation, to providing robust models that can be consumed by product and platform teams.
Own training and fine-tuning of LLMs / seq2seq models: Design and execute training pipelines for transformer-based models (encoder-decoder, decoder-only, retrievalaugmented, etc.), and fine-tune open-source LLMs on our company-specific data (security content, logs, incidents, customer interactions).
Apply advanced LLM training techniques such as instruction tuning, preference / contrastive learning, LoRA / PEFT, continual pre-training, and domain adaptation where appropriate.
Work deeply with data: define data strategies with product, research and domain experts; build and maintain data pipelines for collecting, cleaning, de-duplicating and labeling large-scale text, code and semi-structured data; and design synthetic data generation and augmentation pipelines.
Build robust evaluation and experimentation frameworks: define offline metrics for LLM quality (task-specific accuracy, calibration, hallucination rate, safety, latency and cost); implement automated evaluation suites (benchmarks, regression tests, redteaming scenarios); and track model performance over time.
Scale training and inference: use distributed training frameworks (e.g. DeepSpeed, FSDP, tensor/pipeline parallelism) to efficiently train models on multi-GPU / multi-node clusters, and optimize inference performance and cost with techniques such as quantization, distillation and caching.
Collaborate closely with security researchers and data engineers to turn domain knowledge and threat intelligence into high-value training and evaluation data, and to expose your models through well-defined interfaces to downstream product and platform teams.

At UVeye, we're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we pioneered the world's first fully automated suite of AI-powered vehicle inspection systems, combining computer vision, machine learning, and generative AI.
With over $380M in funding and strategic partnerships with Toyota, Amazon, General Motors, JLR, Volvo, and Hertz, our technology is deployed across manufacturing plants, dealerships, wholesale auctions, fleets, and seaports worldwide. Named one of Fast Company's Most Innovative Companies of 2026, our 300+ global employees are solutions-oriented, accountable, and driven by one shared goal: making roads safer for everyone.
We are looking for an experienced Senior Deep Learning Engineer with proven capabilities to lead the development of state-of-the-art computer vision products from concept to production. In this role, you will be a part of a highly talented R&D team driving the core of UVeye’s inspection portfolio, while researching and implementing diverse Machine and Deep Learning algorithmic solutions to solve complex, real-world visual challenges.
A day in the life and how you’ll make an impact:
* Design and Development of novel, robust and efficient Machine Learning/ Deep Learning algorithms for major Vision challenges.
* Create Proof of Concepts (PoC) for new products and technologies, transitioning research-grade ideas into scalable, production-ready systems.
* Evaluate, benchmark, and profile different algorithms on unique, large-scale proprietary datasets, while driving data-centric AI methodologies (active learning, data curation).
* Collaborate with infrastructure, MLOps, and hardware teams to define future technology, features, and optimize models for real-time inference constraints (on Edge/Cloud devices).

About the Role
Design, build, and improve ML-powered software products that deliver real value to users.
Explore, analyze, and model large-scale textual data to support accurate predictions, classification, and decision-making.
Develop and evaluate NLP and machine learning models, using LLMs and generative AI techniques when relevant.
Move quickly from data analysis and experimentation to prototypes, production-ready code, and integration with other services.
Own the quality, performance, and ongoing improvement of your work through metrics, evaluation, and data-driven iteration.
Collaborate with product, engineering, and research partners while learning from a strong technical team.

We are seeking an innovative AI Engineer to join our team in building the next generation of security protection and cyber attack detection for endpoints. In this role, you will leverage cutting-edge AI technologies and advanced agentic approaches to revolutionize how cyber threats are identified, analyzed, and mitigated. You will design, build, and optimize intelligent AI agents that analyze complex security data to deliver highly accurate, automated verdict decisions on malicious activities, ensuring endpoint resilience against sophisticated attacks.
Key Responsibilities
Agentic Framework Design: Design and implement intelligent, multi-agent AI systems capable of executing complex security analysis workflows and automated decision-making.
Context Optimization: Analyze diverse security datasets to determine the most effective context, telemetry data, and threat intelligence to feed into AI agents to maximize decision accuracy and minimize false positives.
Model Configuration & Integration: Evaluate, configure, and deploy a variety of state-of-the-art language models and AI architectures tailored for high-performance security use cases.
Data Analysis & Performance Evaluation: Perform deep data analysis on security events and model outputs to continuously refine agent logic, benchmark performance, and optimize AI-driven detection mechanisms.
Collaboration & Deployment: Partner with security research and engineering teams to integrate intelligent AI components into production systems seamlessly and securely.

This is a role in our companys core AI group, which specializes in developing cutting-edge AI solutions in healthcare, enhancing medical imaging and diagnostics. As a Tech Leader in the AI Algorithm Engineering group, you will play a pivotal role in both managing end-to-end AI research and development efforts and hands-on involvement in key-initiatives. Your responsibility will include design, implementation, guidance and mentoring for team members, and representing the AI considerations in cross-team discussions. You will leverage your extensive experience to lead multiple AI projects, and will be a key figure in leading successful execution and in finding creative solutions to difficult bottlenecks, across data, AI, engineering and product considerations.
Responsibilities
Lead the design, development, and implementation of accurate and robust AI algorithms for medical data with a hands-on approach.
Collaborate with cross-functional teams, including data scientists, software engineers, product managers and clinical data experts, to ensure AI considerations have a profound impact on R&D and Product decisions across the projects.
Design and conduct research and experimentation to improve algorithm performance and accuracy.
Stay at the forefront of the latest advancements in AI and machine learning, particularly in the medical domain, and drive their adoption within the team.
Oversee multiple projects, ensuring successful execution, timely delivery and alignment with product and business objectives.
Provide strategic direction and technical mentoring to elevate the capabilities of the AI team.

We are looking for a talented AI Solutions Engineer to join our innovative AI team. The team develops advanced AI platforms and applications including agentic workflows, Retrieval-Augmented Generation (RAG) systems, Large Language Model (LLM) based solutions, AI agents, MCPs, and more. You will have the opportunity to shape how AI transforms our products and internal processes worldwide. Your responsibilities will include implementing state-of-the-art AI technologies, developing all aspects of the project - AI, code, data preparation, evaluation, and deployment. We are looking for a motivated teammate who thrives on solving complex problems with AI and continuously explores emerging techniques in this rapidly evolving field.

What you'll be doing:

Design and implement Agentic platforms and workflows to simplify the agentic experience across the company.

End-to-end solutions Implementation to increase the organization quality and productivity.

Develop AI solutions that integrate seamlessly with existing products and workflows.

Build evaluation frameworks to measure and improve AI system performance.

Collaborate with cross-functional teams to identify and implement AI opportunities.

Collect and prepare data from multiple large scale sources for AI training and inference.

Were hiring an AI Backend Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.
This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.
What You Will Do:
Lead & Mentor: Manage, mentor, and grow a team of AI/ML/Backend engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.

Were looking for a Senior Applied AI Engineer who combines deep data science expertise with the engineering skills to turn research into reliable, production-ready products.
Youll be a hands-on technical leader, owning significant AI capabilities from problem definition, academic survey, and system design through research, experimentation, deployment, and continuous improvement. Your work will span classical machine learning, large-scale data analysis, and AI agents that power brand intelligence, market research, and performance marketing.

You should have a track record of driving complex projects, not just contributing to them, and be comfortable making technical decisions, navigating ambiguity, and delivering in a fast-moving startup environment. Youll build systems that Fortune 500 marketing teams rely on to make consequential business decisions.
Responsibilities
Own AI capabilities end to end. Translate business and product needs into well-defined problems, research plans, and technical designs. Take solutions from initial exploration through production deployment and ongoing improvement.
Develop and improve our core algorithms.
Build production-grade AI agents - performance marketing, market research agents, auto-ML agents.
Turn research into maintainable software. Build reusable modules, data pipelines, and services with clear interfaces, automated tests, and robust deployment practices-not just standalone prototypes.
Own quality and performance in production. Monitor system behavior, investigate failure cases, and continuously improve accuracy, reliability, latency, and cost as usage and data volumes grow.
Drive technical decisions and execution. Choose the right approach for each problem, balancing statistical methods, classical ML, and LLM-based systems. Make explicit trade-offs between research depth, delivery speed, and operational complexity.
Provide hands-on technical leadership. Partner with product and engineering to shape priorities, lead technical initiatives, review designs and code, and mentor teammates.