R&D Technical Lead
India
Nokia
As a technology leader across mobile, fixed and cloud networks, our solutions enable a more productive, sustainable and inclusive world.Family Description
Applied R&D (AR) consists of target-oriented research either with the goal of solving a particular problem / answering a specific question or for multi-discipline design, development, and implementation of hardware, software, and systems including maintenance support. Supplies techno-economic consulting to clients. AR work is characterized by its detailed and complex nature in order to systematically combine existing knowledge and practices to further developing and incrementally improving products, operational processes, and customer-specific feature development.
Subfamily Description
Software (SWA) comprises the definition, specification, and allocation of requirements from different sources utilizing knowledge of systems engineering processes (specification & architecture). Contains processing of use case and feature requirements into conceptual models, operational scenarios, technical requirements, and functional description. Covers specification, design, implementation, and unit testing of Software (e.g. device drivers, microcode, hardware-related software & firmware) according to the requirements and architecture defined in the systems engineering process. Covers establishment and maintenance of Software Configuration Management (SCM) practices into software development projects, continuously building and integrating infrastructure tools and systems.
As a Developer(AI/ML) specializing in the telecom domain, you will design, develop, and implement machine learning models and AI solutions to optimize network performance, enhance customer service, and drive strategic insights. You will collaborate with cross-functional teams to deliver data-driven solutions that address complex challenges in the telecommunications industry.
Key Responsibilities:
- Design, develop, and deploy machine learning models using Python to solve specific business problems in telecom industry.
- Analyze large datasets to build predictive models to enhance decision making process.
- Implement and validate machine learning models using various frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Implement containerized ML inferencing solutions using Kubernetes.
- Automate ML and data pipelines to streamline model training and deployment processes.
- Manage the end-to-end ML development lifecycle, from data collection and preprocessing to model training, evaluation, and deployment.
- Develop and deploy neural network or LSTM-based models for various applications.
- Utilize cloud platforms such as Redhat OpenShift, Azure, GCP, or AWS for ML model development and deployment.
- Collaborate with cross-functional teams to integrate ML solutions into production environments.
- Monitor, evaluate and optimize the performance of deployed models and improve the accuracy and efficiency.
- Stay updated with the latest advancements in machine learning and related technologies
- Understanding and adapting different LLM models.
Required Skills and Qualifications:
- 2-5 years of experience in machine learning and related technologies.
- Proficiency in Python programming.
- Hands-on experience with Kubernetes for deploying containerized ML applications.
- Strong understanding of ML and data pipeline automation.
- Proven experience in the full ML development lifecycle.
- Expertise in developing and deploying neural network or LSTM-based models.
- Familiarity with cloud ML platforms such as Azure, GCP, or AWS.
- Excellent problem-solving and analytical skills.
- Strong communication and teamwork abilities.
- Exposure to Generative AI (GenAI) development and tools.
- Experience with other programming languages or frameworks related to ML.
- Proven experience in AI/ML development, preferably in the telecom domain.
- Knowledge of big data technologies and tools.
- Strong programming skills in languages such as Python, R, or Core Java.
- Proficiency in machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience with data manipulation and analysis tools (e.g., SQL, Pandas, NumPy).
- Familiarity with telecommunications concepts and technologies (e.g. 4G, 5G, IoT, network management etc).
Come create the technology that helps the world act together
Nokia is committed to innovation and technology leadership across mobile, fixed and cloud networks. Your career here will have a positive impact on people’s lives and will help us build the capabilities needed for a more productive, sustainable, and inclusive world.
We challenge ourselves to create an inclusive way of working where we are open to new ideas, empowered to take risks and fearless to bring our authentic selves to work
What we offer
Nokia offers continuous learning opportunities, well-being programs to support you mentally and physically, opportunities to join and get supported by employee resource groups, mentoring programs and highly diverse teams with an inclusive culture where people thrive and are empowered.
Nokia is committed to inclusion and is an equal opportunity employer
Nokia has received the following recognitions for its commitment to inclusion & equality:
- One of the World’s Most Ethical Companies by Ethisphere
- Gender-Equality Index by Bloomberg
- Workplace Pride Global Benchmark
At Nokia, we act inclusively and respect the uniqueness of people. Nokia’s employment decisions are made regardless of race, color, national or ethnic origin, religion, gender, sexual orientation, gender identity or expression, age, marital status, disability, protected veteran status or other characteristics protected by law.
We are committed to a culture of inclusion built upon our core value of respect.
Join us and be part of a company where you will feel included and empowered to succeed.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Azure Big Data Consulting Data pipelines Engineering GCP Generative AI Java Kubernetes LLMs LSTM Machine Learning ML models Model training NumPy Pandas Pipelines Python PyTorch R R&D Research Scikit-learn SQL TensorFlow Testing
Perks/benefits: Career development
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