דרושים » דאטה » Senior staff AI scientist, FILM Team

We are looking for a Machine Learning Engineer (MLE) to work on building foundational language models and agentic AI systems that empower small and medium-sized businesses (SMBs) in their financial and operational journeys.
In this role, youll work alongside Machine Learning Engineers, AI scientists and product teams to build LLM based solutions for millions of small and medium busniesses around the world, and build foundational models, involving translate breakthrough research into production systems - designing, implementing, optimizing cost, latency, serving models that reason, act, and learn across real-world business contexts. Youll build scalable pipelines and infrastructure that drive impact on customers lives with the state-of-the-art AI from prototype to customer impact.
This is a unique opportunity for an engineer who thrives at the intersection of science and production, combining deep technical understanding of AI systems with the rigor and creativity needed to deliver robust, reliable, and high-performing products at scale.
Responsibilities:
Implement, optimize, and deploy foundation and agentic models for large-scale use in financial reasoning, decision support, and business automation.
Collaborate with MLE, AI scientists to operationalize research ideas, turning model architectures and training methods into efficient, production-grade implementations.
Design, build, and maintain ML pipelines for data ingestion, preprocessing, training, evaluation, and continuous improvement.
Optimize inference efficiency and model latency, ensuring production systems meet real-time performance requirements.
Contribute to retrieval, memory, and orchestration components that enable agentic reasoning and long-term context management.
Establish best practices for model monitoring, evaluation, and safe deployment, including automated testing and observability in production environments.
Drive applied innovation, bridging the gap between research prototypes and large-scale, reliable business solutions used by millions of customers.

Join an amazing team driving AI solutions in the fintech industry, primarily focused on evaluating risk for lending products.
This Senior Staff role is a blend of leading the full AI/ML development cycle and acting as a Data Science Architect, responsible for all engineering aspects of the work to deliver excellent, high-quality, and operationally sound AI systems.
Responsibilities:
System Architecture & Operational Excellence:
Deliver robust AI/ML system designs that meet customer and systems requirements, including latency, throughput, cost, and maintenance.
Working with partners and architects, define the vision and align on architecture for integration, ensuring excellent deliveries in terms of quality, stability, security, compliance, and operational excellence.
Drive cross-functional end-to-end design architecture.
Lead conversations with partner architects to influence AI-driven product design and strategy
AI/ML Development & Modeling:
Lead the full cycle of iterative big data exploration, including hypothesis formulation, algorithm development, data cleansing, testing, and insight generation.
Apply advanced, predictive statistical modeling and testing to extract data-driven insights from complex, large-scale data sources (relational and non-relational).
Review complex and challenging work to help simplify and execute with speed.
Strategy & Consultation:
Provide guidance to business stakeholders on how best to harness available data and fully exploit the insights revealed through the research.
Drive the design and creation of reusable AI capabilities.

We are seeking a Senior Data Scientist to be one of the first data science hires for our newly formed ML team. This is a unique ground-floor opportunity to build our data science capabilities from scratch and have direct influence on our analytical and modeling approaches. This role combines advanced data science expertise with foundational contributions, requiring someone who can develop sophisticated models, conduct deep analytical research, and help establish the data science methodologies that will guide the team as we scale. As one of our founding data scientists, you'll work closely with our Tech Lead to shape our modeling approaches, define our analytical standards, and build the fundamental data science skill set for future hires.
What You'll Do:Empty heading
Build foundational data science capabilities: As one of our first data science hires, work with the Tech Lead to develop core modeling methodologies, analytical frameworks, and research practices
End-to-end model development: Take ownership of complete ML model lifecycle - from initial research and experimentation through production deployment and monitoring
Build impactful models: Design, develop, and deploy machine learning models that solve complex business problems across payments, risk, and customer analytics
Define analytical standards: Help establish best practices for data exploration, feature engineering, model validation, and statistical analysis
Conduct deep research: Lead exploratory data analysis and research initiatives to uncover insights and identify ML opportunities across the business
Partner with stakeholders: Work closely with business teams to understand requirements, translate problems into data science solutions, and communicate findings effectively
Establish model development practices: Help set up our approach to model experimentation, A/B testing, and performance monitoring
Shape data science culture: Contribute to establishing the team's analytical rigor, documentation standards, and knowledge-sharing practices
Drive innovation: Research and evaluate new ML techniques, algorithms, and approaches that could benefit our business use cases.

Come join as a Senior Staff Machine Learning Engineer (MLE).
Senior Staff MLEs deliver end-to-end AI solutions that span multiple domains and products, influencing the strategic direction of machine learning and AI across the company. You will identify cross-cutting opportunities, set technical direction for complex systems, and deliver scalable, responsible AI-driven experiences that unlock customer and business value at scale.
In this role, youll be expected to define and evolve ML architecture, guide multiple teams, and drive execution excellence across the full ML lifecycle-from experimentation to production. Youll partner closely with AI scientists, product engineers, and business leaders to solve high-impact problems and pioneer new capabilities that advance AI-native platform.

We are looking for team members that love new challenges, cracking tough problems, and working cross-functionally.
You will be working end-to-end from ideation to implementation and have an opportunity to see your models make a significant impact on products and customers security.
Responsibilitie:
Develop ML models to identify security exploits, that based on a wide range of algorithms and techniques (classification, clustering, graph based)
Explore various data sources while leveraging your domain knowledge to craft creative features to boost model performance
Lead and innovate AI projects in the Security domain, lead discussions and understand the needs of the project from the business units and be able to integrate your domain knowledge into the algorithms you'll build and implement in production
Be an active partner of the full cycle of iterative big data exploration, including hypothesis formulation, algorithm development, data cleansing, testing, insight generation, and visualization

Were seeking a Team Lead Generative AI Engineer to lead a team of engineers in designing, developing, and deploying production-grade AI systems. This role is ideal for someone who is both a strong technical contributor and an experienced people leadercapable of driving architecture decisions, mentoring team members, and delivering innovative AI solutions at scale.
You will be responsible for guiding the end-to-end lifecycle of Generative AI applications, ensuring technical excellence, scalability, and alignment with business needs. This includes working across backend systems, RAG pipelines, prompt engineering, and cloud-native deployments.
Key Responsibilities
Leadership & Team Management Lead and mentor a team of AI/ML engineers, fostering growth and technical excellence.
Define and enforce coding standards, architectural patterns, and best practices.
Collaborate with stakeholders to translate business needs into AI-driven solutions.
Manage project timelines, technical risks, and team deliverables.
Generative AI & Prompt Engineering Integrate and optimize applications using LLM provider APIs (OpenAI, Anthropic, etc.).
Design prompts with advanced techniques (few-shot, chain-of-thought, chaining, context crafting).
Implement safeguards (guardrails, structured output validation, injection protection).
Architecture & Backend Development Build scalable backend services in .NET (C#) and Python, working with SQL and APIs.
Develop and manage RAG pipelines, conversational AI systems, and summarization tools.
Drive observability: tracing, logging, monitoring for LLM-powered systems.
Evaluation & Optimization Benchmark and evaluate LLMs using custom datasets and automated testing.
Oversee system reliability, performance tuning, caching, and optimization.
Ensure solutions meet enterprise-grade standards for security and scalability.