Data Science ML/Gen AI Engineer – Mid-Level

🔥 0 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 16%

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Irth Solutions

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 1995

☁️ SaaS

⚡ Energy

📡 Telecommunications

💰 Private Equity Round on 2015-07

SaaS • Energy • Telecommunications

Irth Solutions is a market-leading provider of a SaaS platform focused on enhancing resilience and reducing risk in the management of critical network infrastructure. Their solutions are trusted by energy, utility, and telecom companies across the U. S. and Canada, offering capabilities in damage prevention, training, asset inspections, land management, and 811 ticket management. By leveraging business intelligence, analytics, and geospatial data, Irth Solutions provides comprehensive situational awareness to proactively manage and mitigate risks in network infrastructure. The acquisition of OneBridge Solutions enhances their asset performance management offerings.

📋 Description

• Contribute to medallion architecture pipelines (Bronze → Silver → Gold) using Databricks • Implement data quality checks, validation gates, data contracts, column-level lineage, policy-as-code, PII masking, obfuscation, and access controls • Collaborate with data engineering and governance teams to improve data reliability, discoverability, and documentation • Explore, prototype, evaluate, and productionize machine learning and GenAI solutions for forecasting, anomaly detection, NLP, RAG, LLM-powered assistants/copilots, and predictive analytics • Package and manage models using Unity Catalog model management/registries • Design batch and streaming inference architectures • Define success metrics, KPIs, and A/B testing strategies with Product and business stakeholders • Move successful experiments from prototype to production with SLAs, monitoring, documentation, and operational runbooks • Build production workflows, jobs, and notebooks as infrastructure/assets-as-code using Databricks Asset Bundles (DABs) • Implement CI/CD pipelines using GitHub Actions • Design reliable, observable, scalable, and cost-efficient data and ML workloads • Implement proactive monitoring and alerting, automate incident creation and tracking through Jira, and apply FinOps principles • Contribute business metrics, definitions, and semantic models to Unity Catalog • Support consumption through Power BI and Databricks AI/BI • Develop and maintain trusted data products with domain teams • Implement secure data and ML architectures using RBAC and ABAC within Unity Catalog • Manage credentials and secrets using Azure Key Vault or KMS • Support SOC 2, ISO 27001, GDPR, and PIPEDA compliance requirements • Produce audit evidence for data lineage, access reviews, data retention, security controls, and disaster recovery testing • Participate in governance and security reviews and remediate identified gaps • Partner with Product, Data Engineering, Platform, and domain teams to deliver measurable customer and business impact

🎯 Requirements

• 3–6 years of experience in Data Science, Machine Learning, or ML Engineering, with a proven track record of taking models from development through production • Strong programming and data skills in Python, SQL, and Spark/PySpark • Hands-on experience with Databricks, including Delta Lake, Unity Catalog, Databricks SQL (DBSQL), Jobs and Workflows, and Medallion architecture • Strong understanding of ML fundamentals, including feature engineering, model training and selection, model evaluation and validation, model monitoring, data-quality monitoring, and model and data drift detection • Practical GenAI/LLM experience, including prompt engineering, Retrieval-Augmented Generation (RAG), vector databases/vector stores, LLM evaluation, AI safety and guardrails, and LLM latency, scalability, and cost tradeoffs • Experience implementing CI/CD for data and ML workloads, including GitHub Actions, Databricks Asset Bundles (DABs), DEV → QA → PROD environment promotion, and secrets and configuration management • Experience with data contracts and data-quality frameworks, including schema governance, automated expectations/testing, validation, and quarantine/error-handling workflows • Strong understanding of data security and compliance, including PII handling and protection, RBAC/ABAC, data residency requirements, and policy-as-code • Strong communication and collaboration skills with Product, Engineering, Data, and domain teams • Ability to produce technical documentation, including Architecture Decision Records (ADRs), runbooks, experiment reports, and operational documentation • Preferred: Microsoft Azure, AWS, geospatial data and analytics, streaming and real-time data, MLflow, Unity Catalog Model Serving, data and ML observability, FinOps, DR/BCP, resilience practices, and utilities, energy, infrastructure, or public works experience • Nice to have: predictive/risk-scoring/failure-prediction models, anomaly detection, time-series forecasting, GIS/geospatial asset data, asset-integrity data, regulatory/compliance/audit reporting, and operational risk indicators

🏖️ Benefits

• Competitive compensation package based on experience and qualifications • Medical, Dental, and Vision Insurance • 401(k) Plan with Company Match • Generous Paid Time Off (PTO) • Company-Paid Holidays • Flexible Work Options / work-from-home opportunities, depending on role and business needs • On-Call Compensation for eligible on-call shifts