About the Opportunity:
Ericsson Enterprise Wireless Solutions (BEWS) is responsible for driving Ericsson's Enterprise Networking and Security business. Our expanding product portfolio covers wide area networks, local area networks, and enterprise security. We are the #1 global market leader in Wireless-WAN enterprise connectivity and are rapidly growing in enterprise Private 5G networks and Secure Access Services Edge (SASE) solutions.
What Will You Do:
Lead the design and implementation of machine learning and statistical models to solve complex business problems across multiple domains.
Architect and build Agentic AI systems - including multi-agent pipelines, autonomous reasoning loops, tool-using agents, and agent orchestration to enable proactive, self-directed network operations.
Design and deploy LLM-powered applications including RAG pipelines, fine-tuned domain models, prompt engineering strategies, structured output generation, and evaluation frameworks (LLM-as-judge, RAGAS, etc.).
Collaborate with cross-functional teams - data engineers, product managers, and architects - to identify high-impact opportunities for AI-driven solutions and translate them into production-grade systems.
Perform data exploration, feature engineering, and dataset curation to support both classical ML model development and LLM grounding/context pipelines.
Evaluate model performance using rigorous metrics, and ensure interpretability, fairness, and robustness across model types - from tree-based models to transformer architectures.
Contribute to reusable AI frameworks, internal tooling, and shared libraries to raise engineering velocity across the team.
Stay at the forefront of AI/ML research - actively tracking arXiv, open-source releases, and industry developments
What You Will Bring:
8-14 years of applied Data Science and Machine Learning experience, with demonstrated progression in scope and complexity of owned systems.
Deep expertise in classical ML - regression, classification, clustering, ensemble methods, time-series modeling, and anomaly detection - with strong intuition for when to apply them.
Hands-on experience building LLM-based systems: RAG architectures, prompt engineering, context window management, vector databases, and LLM orchestration frameworks
Practical experience designing Agentic AI workflows - including tool-calling agents, memory architectures
Proficiency in model fine-tuning techniques: LoRA, QLoRA, PEFT, instruction tuning, and RLHF/DPO alignment approaches.
Strong programming skills in Python, with proficiency in SQL and familiarity with distributed data processing
Solid software engineering discipline - clean, well-tested, reproducible code with CI/CD awareness.
Experience deploying and scaling AI models in production with robust monitoring, observability, and performance management.
Proven track record of end-to-end ownership of AI/ML projects - from problem framing through production deployment and iteration.
Preferred Qualifications:
Master's or PhD in Computer Science, Statistics, Mathematics, or a related field.
Experience with deep learning frameworks (PyTorch, TensorFlow) and training or fine-tuning large models.
Familiarity with model safety, guardrails, and responsible AI practices, including output filtering, hallucination mitigation, and bias evaluation.
Experience with function calling / tool use patterns in LLMs and building structured, reliable agent behaviors.
Domain exposure in telecom, network operations, or AIOps is highly desirable.
Contributions to open-source AI projects or published research is a plus.
"All academic credentials must be from recognized and accredited institutions and are further subject to verification."
What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like.We encourage you to consider applying to jobs where you might not meet all the criteria. We recognize that we all have transferrable skills, and we can support you with the skills that you need to develop.Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.
Primary country and city: India (IN) || Bangalore
Job details: Developer
Job Stage: Job Stage 7
Primary Recruiter: Shibani Mandal
Hiring Manager: Anupama Muraleedharan
Skills Required
- 8-14 years applied data science and machine learning experience with increasing scope
- Deep expertise in classical ML: regression, classification, clustering, ensembles, time-series, anomaly detection
- Hands-on experience building LLM-based systems (RAG, context management, vector DBs, orchestration)
- Practical experience designing Agentic AI workflows including tool-calling agents and memory architectures
- Proficiency in model fine-tuning techniques (LoRA, QLoRA, PEFT, instruction tuning, RLHF/DPO)
- Strong programming skills in Python
- Proficiency in SQL
- Familiarity with distributed data processing
- Software engineering discipline: clean, tested, reproducible code and CI/CD awareness
- Experience deploying and scaling AI models in production with monitoring and observability
- Proven track record of end-to-end ownership of AI/ML projects
- Master's or PhD in CS, Statistics, Mathematics or related
- Experience with deep learning frameworks and training/fine-tuning large models (PyTorch, TensorFlow)
- Familiarity with model safety, guardrails, hallucination mitigation, and bias evaluation
- Domain exposure in telecom, network operations, or AIOps
- Contributions to open-source AI projects or published research
What We Do
Ericsson builds the digital connectivity the world relies on. Our technology underpins the mobile networks, platforms, and systems that billions of people, businesses, and societies depend on every day. We are a global leader in communications technology, delivering mobile network infrastructure, cloud software, and wireless connectivity solutions for service providers and enterprises worldwide. Our networks support connectivity across 180+ countries, helping power everyday communication as well as critical digital services at global scale. Connectivity has evolved far beyond consumer mobile use. Today, nearly 80% of the world’s population accesses the internet via mobile networks, and Ericsson is helping shape what comes next. We are advancing 5G and 5G Advanced, developing network APIs that open connectivity to the global developer ecosystem, and applying automation and AI to make networks more intelligent, efficient, and resilient. Ericsson was the first company to launch live 5G networks on five continents, and our 5G platform is now commercially live in 150+ networks across 60+ countries. We also support more than 36,000 enterprise customers, enabling secure, high-performance connectivity for industries such as manufacturing, aviation, logistics, utilities, and public safety, where reliability and performance are mission critical. Innovation is central to how we work. Ericsson has approximately 28,000 employees in research and development, backed by one of the strongest intellectual property portfolios in the industry with 60,000+ granted patents. Our engineers, researchers, and technologists work across 100+ global R&D sites, helping define how networks evolve and how digital infrastructure is built for the long term. As the world moves toward a mobile-first, AI-powered, and cloud-driven future, connectivity becomes the foundation for digital transformation across every industry. Ericsson is building that foundation, shaping the future of digital connectivity through technology that operates at global scale and supports real-world impact, today and for what comes next.
Why Work With Us
Ericsson is a place for people who want to work on technology that powers everyday life. You’ll contribute to large-scale systems used every day, tackle complex challenges in live environments, and keep developing your skills and career in your own vision.
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