{"id":2421312,"url":"https://alion.io/job/ericsson-senior-data-scientist","title":"Senior Data Scientist","company":{"id":56456,"name":"Ericsson","domain":"ericsson.com","url":"https://alion.io/company/ericsson","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":80,"open_postings":79,"ghost_share":0,"stale_share":0.785,"repost_share":0,"time_to_fill_p50_days":32,"computed_at":"2026-10-13T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":26000,"max_usd":54000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":55},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"CI/CD","optional":false},{"name":"DPO","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Interpretability","optional":false},{"name":"LLM","optional":false},{"name":"LoRA","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"PEFT","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"QLoRA","optional":false},{"name":"RAG","optional":false},{"name":"RLHF","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Tool Use","optional":false},{"name":"AIOps","optional":true},{"name":"Hallucination","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-10-07T05:55:05Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-13T12:34:02Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"Join our Team\nAbout the Opportunity:\nEricsson Enterprise Wireless Solutions (BEWS) drives Ericsson's Enterprise Networking and Security business. Our growing portfolio spans WAN, LAN, and enterprise security solutions. We are the global leader in Wireless-WAN enterprise connectivity and are rapidly expanding our Private 5G and Secure Access Service Edge (SASE) offerings.\nWhat Will You Do:\nLead the design and deployment of machine learning and statistical models that solve complex business challenges.\nArchitect and build Agentic AI solutions including multi-agent systems, autonomous reasoning loops, tool-using agents, and orchestration frameworks for intelligent network operations.\nDesign and implement LLM-powered applications using RAG, domain-adapted models, prompt engineering, structured outputs, and evaluation frameworks such as RAGAS and LLM-as-Judge.\nPartner with data engineers, product managers, and architects to identify high-value AI opportunities and deliver scalable production solutions.\nPerform data exploration, feature engineering, and dataset preparation for ML and LLM-based systems.\nEvaluate model performance and ensure robustness, interpretability, fairness, and reliability across traditional ML and transformer-based models.\nDevelop reusable AI frameworks, tools, and libraries that improve team productivity and solution quality.\nStay current with advancements in AI/ML research, open-source technologies, and industry trends.\nWhat You Will Bring:\n8-14 years of experience in Data Science and Machine Learning with increasing ownership and technical leadership.\nStrong expertise in regression, classification, clustering, ensemble methods, time-series analysis, and anomaly detection.\nHands-on experience building LLM solutions using RAG, prompt engineering, vector databases, context management, and orchestration frameworks.\nExperience designing Agentic AI workflows, including tool-calling agents, memory architectures, and autonomous decision-making systems.\nKnowledge of model fine-tuning techniques including LoRA, QLoRA, PEFT, instruction tuning, and RLHF/DPO approaches.\nStrong programming skills in Python, proficiency in SQL, and familiarity with distributed data processing platforms.\nSolid software engineering practices with clean, testable, reproducible code and CI/CD awareness.\nExperience deploying, monitoring, and scaling AI models in production environments.\nProven track record of leading AI/ML initiatives from problem definition through deployment and continuous improvement.\nPreferred Qualifications:\nMaster's or PhD in Computer Science, Statistics, Mathematics, or a related discipline.\nExperience with deep learning frameworks such as PyTorch and TensorFlow, including training or fine-tuning large models.\nUnderstanding of responsible AI practices, model safety, guardrails, hallucination mitigation, bias evaluation, and output filtering.\nExperience with function-calling and tool-use patterns in LLM applications and reliable agent design.\nExposure to telecom, network operations, AIOps, or related domains is highly desirable.\nContributions to open-source projects or published research are an advantage.\nAll academic 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