This is a AI Software Tech Lead, ML role within our companys AI Engineering group, focused on building and scaling the infrastructure behind advanced AI solutions in computer vision and NLP for medical imaging. The role combines hands-on software development, technical leadership, and close collaboration with cross-functional teams to transform AI innovation into scalable, high-impact products.
Responsibilities
Design, develop and lead SW development of infrastructure for innovative AI algorithms for computer vision and NLP in the context of medical imaging.
Collaborate with cross-functional teams, including researchers and product managers, to drive the development of new AI products and features.
Work in a unique professional culture applying the full range of software engineering capabilities in the core parts of the A.I. systems
Develop and maintain high-quality, scalable, and efficient code.
Take initiative in exploring and adopting of new technological advances in all relevant domains (for example, scalable cloud based systems, DL and CV SW frameworks, Large scale ML systems).

This is a Senior AI Software Engineer role within our companys AI Engineering group, focused on building and scaling the infrastructure behind advanced AI solutions in computer vision and NLP for medical imaging. The role combines hands-on software development, technical leadership, and close collaboration with cross-functional teams to transform AI innovation into scalable, high-impact products.
Responsibilities
Design, develop and lead SW development of infrastructure for innovative AI algorithms for computer vision and NLP in the context of medical imaging.
Collaborate with cross-functional teams, including researchers and product managers, to drive the development of new AI products and features.
Work in a unique professional culture applying the full range of software engineering capabilities in the core parts of the A.I. systems
Develop and maintain high-quality, scalable, and efficient code.
Take initiative in exploring and adopting of new technological advances in all relevant domains (for example, scalable cloud based systems, DL and CV SW frameworks, Large scale ML systems).

This is a Principal AI Software Engineer role at the heart of our companys AI Engineering group-where algorithms, infrastructure, and products intersect. Youll lead the evolution and scaling of our companys AI architecture, ensuring reliability, efficiency, and impact across global clinical workflows. The role combines technical depth with cross-functional influence, strengthening how our AI systems are built, integrated, and delivered to drive ongoing impact for patients and care teams.
Responsibilities
Lead cross-domain engineering initiatives connecting AI algorithms (CV, NLP, and deep-learning systems), software, and data systems-from design to delivery.
Stay hands-on, contributing to AI-serving (training and inference), integration, and orchestration components while setting high technical standards.
Partner with Algo teams to connect algorithmic innovation with strong system design, ensuring smooth delivery across Product and Engineering.
Guide architectural evolution, ensuring efficiency, consistency, and maintainability across AI workflows.
Communicate direction and priorities clearly, aligning teams around technical goals.
Mentor engineers and promote technical excellence, sound design, and shared best practices.
Foster collaboration and shared ownership, helping maintain a culture that values clarity, curiosity, and technical excellence.
Uphold quality and reliability-including clean code, testing, and CI/CD discipline-while evaluating and adopting new tools that enhance performance and long-term scalability.

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.

This is a leadership role within our companys core AI group, focused on building and evolving the AI-facing software systems that enable our algorithms to move from research into robust, production-ready components.
The AI Software team is responsible for developing the software layers, tooling, and core systems that support the development, execution, and operational readiness of AI models throughout their lifecycle. As a Team Lead, you will shape the teams technical direction, guide execution, and remain deeply hands-on, contributing to architecture, implementation, and key technical decisions.
You will lead a scrum team, work closely with AI researchers and algorithm engineers, and collaborate with product and engineering partners. The role combines strong software engineering with AI context, in a culture where software quality is a core enabler of AI excellence, and technical leadership is grounded in ownership, clarity, and impact.
Responsibilities
Lead the teams work on core software systems that sit at the intersection of algorithms and engineering, owning their design and implementation as part of the overall solution.
Guide and support team members growth, providing technical leadership, mentoring, and day-to-day coaching while fostering ownership and accountability.
Stay deeply hands-on in design and implementation, contributing code and solving complex software engineering problems where impact is highest.
Collaborate closely across teams, working with algorithm engineers, Product, and Engineering partners to define interfaces and align priorities.
Own project-level architecture and technical decisions, ensuring high-quality systems through sound design, code reviews, testing practices, and clear documentation.

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.

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.

As a Senior Applied AI Engineer, you will lead the bridge between cutting-edge AI capabilities and production-grade software. You will design, build, and optimize the intelligent systems, agentic workflows, and LLM-driven architectures that power our companys conversational products.
Also, you will combine software engineering rigour with state-of-the-art Generative AI techniques - optimizing for conversational quality metrics, latency, and system reliability in high-scale production environments, serving millions of users. We are looking for an engineer who is hungry for AI innovation, eager to pioneer new generative capabilities, and passionate about shipping impactful AI solutions.
In this role, you will:
Design & Scale AI Systems: Architect and deploy high-performance LLM orchestration systems, agentic workflows, retrieval-augmented generation (RAG) pipelines, and AI microservices.
Bridge AI Research & Production: Transform frontier LLM research, foundation models, and generative techniques into robust, production-ready features with high availability and low latency.
LLM Evaluation & Guardrails: Design and implement automated LLM evaluation (evals) frameworks, benchmark suites, and guardrail policies to continuously measure accuracy, reduce hallucinations, and ensure safety across product flows.
Optimize Performance & Cost: Lead latency, throughput, and token-cost optimization strategies across commercial APIs and open-source models.
Set AI Engineering Standards: Elevate software craftsmanship across the team through architectural reviews, code quality, and LLMOps best practices, utilizing the latest AI tools.
Drive Product Innovation: Collaborate closely with product and engineering teams to translate complex human resource and conversational challenges into intelligent software solutions.

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.

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.