Machine Learning Engineer
- Luxoft
- 3 - 7 years
- Mumbai
- 26 days ago
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Job Description
We are seeking a skilled and domain-expert Machine Learning Engineer to develop and deploy data-driven solutions in the context of Digital Oilfield (DOF) systems. The ideal candidate will have a strong foundation in machine learning, model development, and data analytics, with the ability to apply these skills to subsurface and production engineering workflows.This is a hands-on technical role focused on building ML models that enhance forecasting, optimization, and operational decision-making across complex oilfield environments. Experience with agent-based or generative AI systems is a bonus, but not a requirement.
- Develop and maintain machine learning models tailored to oilfield data and engineering processes.
- Work closely with domain experts to understand workflows and identify ML opportunities across production, reservoir, and facility systems.
- Build, train, and deploy models for time series prediction, classification, anomaly detection, or clustering using structured and semi-structured data.
- Validate model accuracy and performance in real-world operational settings.
- Collaborate with software teams to integrate models into DOF platforms or dashboards.
- (Optional but valued) Explore the use of LLMs or agentic AI to support technical queries or enhance interaction with data systems.
- business trip to Kuwait
Must have
- Strong background in machine learning, data modeling, and applied statistics.
- Proficiency in Python and ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
- Familiarity with oilfield datasets, including production data, sensor logs, simulation outputs, or engineering inputs.
- Understanding of the challenges and context of oil & gas workflows, even if not from direct experience.
- Ability to collaborate with geoscientists, production engineers, or field operations teams to co-design effective models.
Nice to have
- Experience working with or developing for Digital Oilfield systems (DOF platforms, custom solutions, or commercial tools).
- Exposure to cloud platforms such as Azure (preferred) or AWS.
- Familiarity with Agentic AI frameworks (LangChain, CrewAI, AutoGen), or LLMs as a support layer in technical environments.
- Knowledge of MLOps practices or tools (e.g., MLflow, Airflow, or model deployment pipelines).
Certifications:
- Azure Data Engineer or AI Engineer certifications are a plus, especially for roles involving cloud-based deployment.
- AWS experience is appreciated but not mandatory
- Location - bangalore.
Job Classification
Industry: LegalFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Machine Learning EngineerEmployement Type: Full timeContact Details:
Company: LuxoftLocation(s): Mumbai
Keyskills: machine learning mlops python data analytics generative ai data engineer forecasting airflow ai cloud platforms ai engineer tensorflow data modeling data systems pytorch clustering aws azure statistics
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