דרושים » תוכנה » Head of Research

In this role, you will lead a team of Machine Learning Scientists and Engineers dedicated to building, training, and deploying cutting-edge Generative AI models. This includes developing foundation models trained on our companys extensive textual data and creating fine-tuned models designed to tackle complex travel-related tasks. Your leadership will play a pivotal role in advancing the application of AI to transform the travel experience for millions of customers.
As a technical manager, you should be passionate about GenAI technology, keep up to date with recent breakthroughs in the field, define and shape the teams ML roadmap, and not be afraid to get your hands dirty with code when needed.
You are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with other stakeholders to define and shape the roadmap of our products. You will work independently and will also be responsible for making technical decisions within your team.
When it comes to management, your expertise in handling people will motivate and inspire them to reach outstanding success! You should have experience in developing people. You will mentor and coach your team while working closely with a Product Manager.
Key Job Responsibilities and Duties:
Leadership in LLM Development- Build, Guide and mentor a team of ML scientists and ML engineers in the development, fine-tuning, and deployment of large language models (LLMs) tailored for the travel domain.
Expertise in the engineering aspects of deploying LLMs at scale with minimal latency. This includes optimizing model performance, scalability, and efficiency to meet the demands of real-time, high-traffic applications.
Define and communicate the technical vision and strategy for LLM-related initiatives, ensuring alignment with company goals and customer needs.
Foster a culture of collaboration, innovation, and excellence within the team.
Prioritize work in collaboration with Product Managers, depending on business needs and keeping stakeholders aligned at all times.
Translate machine learning vision and strategy into planning and execution, and ensure timely delivery of their plans.
Develop innovative ML models, algorithms, and engineering approaches or identify existing ones, with the potential to impact our business.
Design and execute applied research plans to understand, apply, test, evolve, and generalize these technologies into reusable frameworks.
Translate business problems into viable, reliable and robust ML and AI solutions, accounting for constraints of the production environment.
Monitor product health, performance and business impact and act accordingly when requirements are not met.
Identify underlying issues and opportunities across domains and situations that are not obviously related through application of structured thinking and logic.
Solve issues by applying methods and insights gained from a variety of disciplines, navigating a variety of environments.

Were seeking a visionary and technically hands-on AI Team Leader to join Alison.ai and take charge of driving innovation across our core AI systems. As the AI Team Leader, you'll guide the architecture and development of advanced machine learning models that power our video and creative analysis platform.
You will collaborate cross-functionally with product managers, engineering, and business development teams to deliver cutting-edge features that push the boundaries of whats possible in creative performance analysis.
This is a high-impact role for someone who thrives at the intersection of machine learning, product strategy, and creativity.
Key Responsibilities:
Lead the development, deployment, and optimization of machine learning models for video, image, and creative performance analysis.
Architect scalable AI/ML pipelines and infrastructure that support real-time and batch processing of multimedia data.
Guide research and experimentation initiativesidentify new technologies, modeling techniques, and opportunities for innovation.
Mentor and grow a team of machine learning engineers and data scientists as we scale.
Champion AI ethics, fairness, and explainability in our model development and deployment.
Stay ahead of industry trends in generative AI, computer vision, NLP, and Martech innovation, translating insights into competitive advantages.

The ML Detection team is a new, cross-functional team at the core of our product strategy. Its mission is to own and advance the machine learning-based validations that form the foundation of our accessibility testing solutions. This includes everything from data collection and research to deploying, monitoring, and maintaining models in production. You will lead a multidisciplinary team of Data Scientists, ML/Data Engineers, and Algorithm Developers to build foundational models and standalone validations that extend the reach and precision of our products, giving Evinced a critical competitive edge.

Your Impact:

Lead, mentor, and grow a multidisciplinary team of Data Scientists, ML Engineers, and Algorithm Developers, fostering a culture of trust, collaboration, and professional growth.
Own the end-to-end delivery of ML-based detection capabilities, from initial research and data collection to model deployment, monitoring, and algorithmic post-processing.
Provide hands-on leadership, actively contributing to technical solutions, architecture, and design reviews for new algorithms and models.
Collaborate closely with Product, DevOps, and R&D teams to align on priorities, manage integrations, and ensure efficient, impactful development cycles.
Architect and oversee the development of the infrastructure required for the entire ML lifecycle, including data management, experimentation platforms, and model deployment/monitoring systems.
Define and refine team processes, tools, and methodologies to optimize performance, quality, and stability, ensuring data science tasks have clear definitions of done.
Drive the strategic vision for the evolution of our detection capabilities, including UI patterns, interactive elements and accessibility issues, to meet current and future needs.
Act as the primary problem solver and technical resource for the team, guiding them through complex research and engineering challenges.

we are looking for a AI Engineer to join our R&D organization and help lead the development of AI-powered and data-driven capabilities in our Developer Productivity Platform.
In this role, you will transform data into actionable insights and intelligent models that help software teams understand, measure, and improve how they work. Youll work closely with product, data, and engineering teams to design and deliver AI and data science solutions that have real impact on developer productivity and business outcomes.

Key Responsibilities:
Design, develop, and deploy AI-driven features & data science and ML models to analyze code flows, software development processes, team behaviors, and performance metrics.
Build AI & data pipelines and analytical infrastructure that ensure data quality, accessibility, and freshness at scale.
Translate complex data into clear, actionable insights and code analysis that influence product direction and drive customer value.
Develop and maintain predictive, prescriptive, and diagnostic models to support use cases like delivery forecasting, productivity measurement, and team health analysis.
Partner with Product Managers, Data Engineers, and Backend Engineers to bring insights to life through AI & data-driven features and platform improvements.
Monitor and continuously improve model performance through experimentation, A/B testing, and user feedback loops.
Research and evaluate new AI/ML tools and methodologies to enhance the platforms intelligence and scalability.

We are looking for an exceptional MLOps Team Lead to own, build, and scale the infrastructure and automation that powers Labs state-of-the-art Large Language Models (LLMs) and AI systems.
This is a technical leadership role that blends hands-on engineering with strategic vision. You will define MLOps best practices, build high-performance ML infrastructure, and lead a world-class team working at the intersection of AI research and production-grade ML systems.
You will work closely with LLM Algorithm Researchers, ML Engineers, and Data Scientists to enable fast, scalable, and reliable ML workflows covering everything from distributed training to real-time inference optimization.
If you have deep technical expertise, thrive in high-scale AI environments, and want to lead the next generation of MLOps, we want to hear from you.

As a machine learning scientist, your work will focus on building, training and deploying content models (Computer vision, NLP and Generative AI) using the most advanced technologies and models.
You will be responsible for identifying and proposing the most appropriate data sources and modeling techniques to solve complex problems and drive business value.
Key Job Responsibilities and Duties:
Explore and apply state-of-the-art techniques in multimodal machine learning.
Train innovative ML models (NLP, CV, LLM-finetuning), build algorithms, and engineering approaches to drive business impact..
Coding skills: ensure implementation of reusable frameworks (clean and scalable code).
Conduct data analysis with detailed metrics to evaluate models performance, labels quality, features exploration.
Work closely with machine learning engineers to ensure the model's latency/throughput meets product requirements and ensure deployment of your model to production.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

We're looking for a skilled and motivated Data Science Team Lead to guide a team of talented data scientists in developing real-time, machine learning-based products. Youll play a key role in driving innovation - researching, designing, and deploying advanced ML models that directly enhance user experience and product performance.

This is an exciting opportunity for a hands-on leader who thrives in a fast-paced, impact-driven environment.

Responsibilities:

Lead, mentor, and inspire a team of data scientistsfostering a culture of collaboration, innovation, and technical excellence
Guide team members personal and professional development
Collaborate with product and engineering teams to identify challenges, uncover opportunities, and drive data-driven solutions
Recruit and retain top-tier talent as the team grows
Research and develop ML models using cutting-edge techniques across a range of domains
Generate new ideas and insights to improve performance and deliver business value

Were hiring a Machine Learning 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 ML 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 hiring a ML Engineer to accelerate AI-driven innovation across B2B SaaS platform.
Youll be at the forefront of building intelligent systems that power core product experiences and automate internal operations, driving efficiency, speed, and scale across the organization. This is a high-impact, hands-on role in a fast-growing, AI-first company where machine learning is a foundational pillar, not a bolt-on feature. You'll partner with product, engineering, and operations teams to design and implement powerful ML and LLM-based solutions that make a measurable difference.
What You Will Do.:
Build Intelligent Systems: Design and develop ML/LLM-powered solutions that solve real-world challenges across product and internal workflows.
Own Full Lifecycles: Take projects from concept all the way to production, including model training, evaluation, integration, and monitoring.
Leverage State-of-the-Art Tools: Work with leading frameworks like LangChain, Hugging Face, TensorFlow, and PyTorch to deliver cutting-edge functionality.
Collaborate Cross-Functionally: Partner with product managers, engineers, and stakeholders to embed AI capabilities into user-facing features and backend services.
Ship at Scale: Build and maintain scalable APIs and services, integrating best practices in CI/CD, observability, and cloud infrastructure.
Report with Impact: Share progress, challenges, and results clearly with technical and executive stakeholders.

We are looking for a highly skilled AI Engineer with a strong engineering mindset to bridge the gap between research and production.

In this role, you will be responsible for validating AI models developed by our Data Science team against real-world production systems, and then leading their optimization, deployment, and ongoing maintenance.

You will be part of the R&D team, working closely with engineers, data scientists, and product managers to ensure our AI solutions are scalable, reliable, and deliver long-term value.

If you enjoy working at the intersection of AI and engineering bringing models to life in production, optimizing for performance, and building reliable systems this role is for you!

Responsibilities
Lead the transition of AI models from proof-of-concept to full-scale production, ensuring they meet architectural, scalability, and performance standards.
Build observability and troubleshooting tools for AI services in production, including logging, performance tracking, and failure analysis pipelines.
Optimize inference performance, including latency, resource usage, and throughput, while maintaining model quality.
Manage model versioning and deployment readiness, including handoff processes, rollback plans, and configuration management.
Partner with the Data Science team to assess model readiness for production, validate input and output compatibility, and ensure assumptions align with real-world system behavior.
Collaborate cross-functionally with DevOps, backend engineers and data scientists to ensure scalable, secure, and cost-effective deployment of ML models