Senior Data Scientist at Ericsson

Santa Clara, California, United States -

Full Time

Start Date

Immediate

Expiry Date

02 May, 26

Salary

0.0

Posted On

01 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Neural Networks, Natural Language Processing, Transformers, Generative AI, Python, Deep Learning, Data Analytics, Feature Engineering, Model Evaluation, Telecommunications, Collaboration, Agile Methodologies, Cloud Platforms, MLOps, Statistical Analysis

Industry

Telecommunications

Description

Experience & Education: 5-7 years of hands-on experience as a data scientist or AI/ML engineer, with a proven track record of delivering ML solutions end-to-end (from exploration to production). A Bachelor's degree in Computer Science, Data Science, Engineering or related field is required (Master's/Ph.D. preferred). ML/AI Expertise: Deep knowledge of machine learning fundamentals and neural network algorithms, including classic models and modern architectures. You should be well-versed in Transformer networks and NLP/LLM technologies, as well as other AI techniques like CNNs, RNNs, reinforcement learning, etc. Experience building and refining transformer-based LLMs (e.g., GPT-4, LLaMA, etc.) and familiarity with their open-source implementations and APIs is expected. Generative AI & Agents: Hands-on experience with state-of-the-art generative AI tools, fine tuning approaches such as LoRA/GRPO/SFT/RFT, knowledge of MCP and A2A, and platforms - including working with open-source LLMs and APIs (OpenAI, Anthropic, etc.). Knowledge of advanced RAG techniques, prompt engineering, and context engineering for improving LLM responses is highly valued. You should also understand advanced agentic AI concepts (e.g. the ReAct agent paradigm for decision-making) and have exposure to frameworks for building AI agents or autonomous workflows. Programming & Tools: Strong programming skills in Python and proficiency with the modern AI/ML ecosystem. This includes experience with deep learning frameworks (PyTorch, TensorFlow), NLP libraries (HuggingFace Transformers), and AI orchestration frameworks (such as LangGraph or similar) for tool integration. Familiarity with data science notebooks, version control, and MLOps tools for model deployment/monitoring is also important. Data Analytics & Foundations: Demonstrated ability to work with large, complex datasets (including time-series data). Experience in data preprocessing, feature engineering, and vector databases for embeddings is a plus. A solid foundation in mathematics, statistics, and probability is required to develop and validate models. Evaluation & Optimization: Experience in evaluating AI models and designing custom evaluation benchmarks to measure model/agent performance (e.g. testing for accuracy, bias, “hallucination” in LLM outputs, etc.). You continually iterate on models based on quantitative metrics and error analysis, and you are familiar with AI safety or reliability considerations in model development. Domain Knowledge: Basic understanding of telecommunications networks - including Radio access networks (RAN), Transport, and Core network domains. You have an interest in how AI can be applied to network optimization, operations, and automation; for instance, how AI-powered rApps (Radio apps) or agents can improve network performance and orchestrate resources autonomously. (Telecom/IoT domain knowledge is a strong plus.) Collaboration & Communication: Excellent problem-solving skills and ability to communicate complex AI concepts to cross-functional teams. You can effectively partner with business stakeholders and engineers, translating requirements into AI solutions and articulating results/insights clearly. Experience working in an agile, collaborative environment on innovative projects is preferred. Familiarity with industry standards (3GPP, O-RAN) and prior experience in network automation or telecom analytics projects is an advantage. Additionally, experience with AI data cloud platforms such as Snowflake and cloud platforms (AWS, Azure, GCP) for scalable ML would be beneficial. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world's toughest problems. You´ll be challenged, but you won't be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. We truly believe this approach drives innovation, which is essential for our future growth. DISCLAIMER: The above statements are intended to describe the general nature and level of work being performed by employees in this position. They are not an exhaustive list of all responsibilities, duties and skills required for this position, and you may be required to perform additional job tasks as assigned. Primary country and city: United States (US) || Santa Clara Job details: Data Scientist (Techn)

Responsibilities

The Senior Data Scientist will be responsible for delivering machine learning solutions from exploration to production, working with complex datasets and evaluating AI models. They will collaborate with cross-functional teams to translate business requirements into AI solutions.