דרושים » תוכנה » ML Engineer

we are searching for world-class researchers in deep learning and natural language processing (NLP) to join our Conversational AI research team. Our team is pushing the boundaries of generative AI by building state-of-the-art large language models (LLM). We work on new neural architectures to enable LLM with very long context, on applying LLM to solve complicated math and coding problems, and on improvement LLM robustness. If you are passionate about the latest research and technologies revolutionizing generative AI and want to explore creative new paradigms for applied foundation models such as reasoning agents, this team will be a great fit for you. After building prototypes that demonstrate the promise of your research, you will collaborate with product teams to apply your ideas into industry-leading real-world applications.
What you will do:
Lead the research on new deep learning algorithms and techniques for efficient LLM inference
Develop new architectures for advanced large language models
Design and adapt foundation AI models to downstream tasks such as math and code reasoning.
Contribute these new models to Nemo framework
Construct and curate datasets for large-scale machine learning, for learning from human preferences, and for specific domains of applications.
Work closely with product and hardware architecture teams to integrate your research and developments into products.

We are seeking talented engineers to join our teams in building cutting-edge products that connect billions of people around the world.
As a member of our team, you will have the opportunity to work on complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we're looking for passionate individuals who can help us advance the way people connect globally. If you're interested in joining a world-class team of engineers and researchers to work on exciting projects that have significant impact, we encourage you to apply.
Software Engineer, Machine Learning Responsibilities
Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences
Implement custom user interfaces using latest programming techniques and technologies
Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews
Set direction and goals for teams, lead major initiatives, provide technical guidance and mentorship to peers, and help onboard new team members
Architect efficient and scalable systems that drive complex applications
Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt
Work on a variety of coding languages and technologies
Establish ownership of components, features, or systems with expert end-to-end understanding.

Our team is looking for a Deep Learning Engineer.
Role and Responsibilities:
Develop Large Language Models as part of our applied research projects and in support of AI21 Platform, including designing, implementing and training massive-scale deep language models
Implement, optimize, scale and test new cutting edge ideas and architectures
Perform large-scale evaluations and comparisons of trained models across a range of benchmarks, as well as adding support for new benchmarks.

We are scaling our AI team with mission-driven individuals eager to shape the future of mobility. As a Machine Learning Model Evaluation Engineer (Computer Vision), youll collaborate closely with our research team to design, build, and optimize data infrastructure and annotation workflows. You will be the focal point between the team and the annotation team, ensuring high-quality labeled data and efficient processes. Additionally, you will help optimize our algorithms, analyze performance metrics, and define optimal operating points to enhance model effectiveness. Your work will directly contribute to pushing the boundaries of Vision AI and advancing our cutting-edge projects.


RESPONSIBILITIES

Model Evaluation
Work closely with the research team to evaluate model performance and define optimal operating points using precision, recall, and other ML evaluation metrics.
Annotation Management
Be the focal point for annotation processes to ensure high-quality labeled data and streamlined workflows.
Database Management
Manage and maintain internal research databases for data-driven decision-making.
Cloud Infrastructure
Develop, maintain, and optimize cloud-based data infrastructure (AWS, GCP).
Benchmarking Framework
Build and maintain a benchmarking framework for continuous algorithm performance evaluation, including human-in-the-loop pipelines.
Dataset Curation
Curate training and testing datasets by querying databases and annotations, and by running data quality and auto-labelling tools.
Model Execution
Run algorithms and deep-learning models at scale.

We are seeking for a talented AI/ML developer with strong focus on Python expertise and hands-on experience in AI/ML models to join our Data Science group. The Data Science group plays a pivotal role in driving the execution and delivery of advanced AI and modern Machine Learning solutions, that empower impactful projects to our target sectors.
Key Responsibilities:
Take part in all development aspects, from concept to production, of AI/ML models and LLM-based features (agents development)
Stay up to date with state-of-the-art research in the field of LLM and apply relevant advancements to improve our solutions
Mentor new team members and share your expertise to strengthen the teams collective knowledge.

We are looking for a Senior ML Engineer.
Responsibilities:
As a Senior Machine Learning engineer at Substrata, you will be working directly with our Head of R&D and will take a major role building our Pragmatic Intelligence Engine using and experimenting with S.O.T.A Deep Learning architectures, including: Multi-Layer Perceptron Neural Network, LSTM, mLSTM, CNN, RNN, VDCNN, etc.

We are looking for experienced, creative and impact-oriented Algorithm Developers to join our team!
As an Algorithm Developer you will be responsible for building state of the art algorithms powering LLMs and agentic frameworks. You will be part of a multi-disciplinary team that also includes engineers and product professionals, all working together to bring our products to life.
You will take part in the full life cycle of our development process, deeply understand the problem we are solving, come up with algorithmic approaches for solving these problems, devise strategies for collecting necessary training data, train and evaluate large language models and other machine learning models and also be in charge of deploying these solutions in production.
Role and Responsibilities:
Build the algorithms that power our various products
Develop production-grade solutions to challenging product-driven NLP tasks by combining language models, RL and classical ML/NLP.
Collaborate with product, sales and customer success teams to define success criteria and translate them into quantitative measures and objectives
Devise innovative strategies for collecting training and evaluation data
Train and evaluate models in realistic production scenarios
End-to-end ownership of the algorithmic components of our products, from design, through implementation and monitoring in production

Required Software Engineer, ML (Technical Leadership)
The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk.
The principal will enable the risk organization to deliver significant lift over current long range objectives for friction and leakage through the generation of new Machine Learning opportunities for the organization and support of successful delivery of the risk management ML architecture. This person will partner closely with the FRM engineering leader (Director level) and be part of our risk management leadership circle.
Software Engineer, ML (Technical Leadership) Responsibilities
Address core business and technical machine learning opportunities: elevate the existing portfolio of machine learning solutions to be state-of-the-art for minimizing our financial losses (due to leakage, good revenues loss and friction). Following are a few examples of technical and business problems we aim to address. - Provide a solution for optimizing the risk machine learning model ensemble (covering the entire end-to-end advertiser funnel including detection, decisioning, enforcement and remediation) through optimization of the current model portfolio and individual models. - Minimize the impact of the prolonged financial fraud feedback loop. - Improve models measurement and performance. - Optimize data/label strategy. - Optimize balance between specific targeted model strategy and broad umbrella model strategy to optimize for short and long term benefits
Lead Research and Introduction of Advanced Technologies: - Collaborate with Financial Integrity's senior ML Engineers to lead the research and introduction of deep learning and Large Language Model (LLM) technologies. - Remain current on industry-wide advancements in ML and introduce relevant advancements in Financial Risk Management
Collaborate on Next-Generation ML Architecture: - Work closely with financial harms principals and risk management tech leads to deliver the next-generation ML architecture for our risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and practices within the FRM team. - Resolve or mitigate design dilemmas, balancing business and technical trade-offs. - Identify and initiate opportunities for collaboration and impact with other organizations
Identify and Initiate New Business Opportunities: - Collaborate with our FinTech, Central Integrity and Core Ads Growth partnerships to identify and initiate new business opportunities based on third-party capabilities. - Conduct proof of concept for different opportunities and initiate integrations to enhance business performance
Grow Other Senior ML Engineers - Actively invest in the growth of other senior ML engineers through goal-driven formal and informal mentorship. Provide regular feedback to other engineers regarding their technical work.

We are seeking a talented Software Development Leader with a strong background in Large Language Models (LLM) and GenAI engineering.
This is a unique opportunity to work with US clients and engage in global projects, leveraging your extensive skills in generative AI tools.
As a pivotal member of our team, you will be responsible for translating complex business problems into data-driven solutions, drafting methodologies, and executing innovative projects. In this role you will:
Lead development of robust, efficient, and scalable Python code, ensuring adherence to best practices in software engineering and optimization for high-performance applications.
Utilize GenAI engineering tools such as LangChain, RAG, Agents, and Vector Database for implementation and optimization.
Stay updated with AI protocols and standards and ensure their correct application in projects.
Collaborate with other teams and team members to understand requirements and develop solutions.
Analyze complex problems, identify and define the computational requirements to solve them.