At SoftServe AI & Data Science group, we lead how AI empowers businesses to grow today and transform what comes next.
In AI & Data Science,
including PhDs
Delivered
across industries
We empower organizations to turn data into decisions and intelligence into impact. Through trusted, responsible innovation, we design and scale AI systems that amplify human potential, accelerate value creation, and shape a future where technology and humanity evolve together.
IURII MILOVANOV
AVP of AI and Data Science, SoftServe
Launched in 2023, the Generative AI Lab is a strategic innovation center where experts work side by side to explore what’s next in AI. Here, you can research and experiment, develop reusable components, pioneer multimodal solutions, and deliver client-centric Generative AI capabilities across industries — turning ideas into practical solutions and testing them in the real world.
SoftServe Digital Concierge, powered by NVIDIA, uses Generative AI to deliver instant, personalized 24/7 support — enhancing customer service and efficiency across industries.
An AI Assistant utilizing generative AI technology designed to engage in real-time conversations with end consumers. It understands their preferences and needs to provide personalized product recommendations.
Deliver real-time guidance, faster troubleshooting, and data-driven insights that boost equipment performance, safety, and operational efficiency.
Solutions that transforms everyday footage into real-time operational insight, helping businesses make faster, smarter, and more proactive decisions.
You grow, and we’re here to make it real. We guide your path with transparent frameworks, clear roadmaps, and mentors who care.Because your journey matters — to you and to us.
Methodological principles for all Data Science profiles
Applies advanced AI techniques, including generative and multimodal models, to extract insights and create predictive and adaptive solutions for diverse business domains. Candidates should have hands-on expertise in modern ML ecosystems, experimentation frameworks, and solving complex data-driven challenges at scale.
Specializes in deploying and scaling AI models by combining software engineering, MLOps, and cloud-native practices. Candidates should be proficient in ML orchestration, pipelines, and Kubernetes, with experience in productionizing foundation and generative AI models.
Shapes the direction of AI initiatives by aligning cutting-edge technologies with business strategy and delivering impactful solutions. Candidates must demonstrate technical excellence, leadership in AI adoption, and the ability to communicate emerging AI opportunities to both technical and non-technical stakeholders.
Guides clients in leveraging the latest AI innovations - such as LLM, Gen AI, and automation frameworks - to achieve strategic outcomes. Candidates should combine deep technical expertise with consulting skills to design adoption roadmaps, drive value realization, and foster long-term partnerships.
Builds and scales robust AI/ML platforms by applying MLOps, cloud-native infrastructure, and lifecycle management for large-scale models. Candidates should demonstrate expertise in deep learning architectures, model optimization, and enterprise-grade deployment to ensure high-performance, reliable AI systems.
Designs end-to-end AI solutions that translate client business objectives into transformative outcomes, leveraging AI capabilities, and responsible AI practices. Professionals in this role must connect strategic vision with technical execution, ensuring that AI adoption delivers measurable impact and long-term value.
Your harmonious and planned career development, supported by clear growth criteria and defined opportunities
Your personal competence development plan with educational materials and training programs
Crystal clear process of improving your performance
Your primary responsibility will be using data science to develop solutions for our clients' complex challenges. This will include creating models, analyzing statistics, and solving problems like Ideation and problem framing, AI adoption, Impact Measurement, and end-to-end implementation according to MLOps best practices. You'll also need to communicate effectively with clients and write efficient code.
Our Data Science group includes over 160 experts in profiles such as Data Scientists, ML Engineers, and ML Architects, with BI and DE working in separate teams.
To keep our team connected and engaged, we hold monthly virtual gatherings and activities across different locations.
A technical mentor is part of the onboarding process for non-senior roles if there is no Data Science technical leader on the project, and managerial support is provided for senior experts. We're flexible about providing mentors for senior roles if needed.
Yes, opportunities for taking on leadership or management roles are discussed after successful onboarding and based on demonstrated skills and expectations.
Edge Computing isn't our primary focus, but our Robotics and IoT CoEs specialize in it. Though they represent a smaller portion of our work, there may be opportunities to work with edge technologies in some projects.
