ML/AI Engineer – Classical ML

Lingaro

. Work with Data Science teams to implement Machine Learning models into production .

Posted 10/7/2026full-timeRemote • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in Data Engineering, focusing on building and implementing Machine Learning models and data processing pipelines. Proficient in MLOps frameworks and cloud services, with strong capabilities in Python development and data architecture.

Highest-signal resume keywords

Data Engineering ExperienceProduction-Ready Python DevelopmentMLOps/LLMOps Tools ProficiencyMachine Learning Model ImplementationData Pipeline Design and Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningPythonMLOpsLLMOpsData ProcessingData Pipeline DesignMachine Learning FrameworksBig Data PlatformsSparkDatabricks

Soft Skills

Good Communication SkillsTeam CollaborationProblem-Solving SkillsCritical ThinkingResponsibility for Tasks

Tools & Technologies

AzureMLAzureAIGCP VertexAIDatabricksEMRHiveSparkData WarehouseData LakeData Integration

Industry Keywords

Machine Learning OperationsAI ArchitectureModel Life CycleData GovernanceModel Efficiency Metrics

Tech Stack

Tools & technologies

AzureCloudGoogle Cloud PlatformMicroservicesPySparkPythonSpark

About the role

Key responsibilities & impact

Work with Data Science teams to implement Machine Learning models into production
Develop practical and innovative LLM/ML/AI automation implementations for scale and efficiency
Design, deliver, and manage industrialized processing pipelines
Define and implement best practices for ML model life cycles and ML operations/LLM operations
Implement AI/MLOps/LLMOps frameworks and support Data Science teams with best practices
Gather and apply knowledge of modern ML Architecture and Operations techniques, tools, and frameworks
Gather technical requirements and estimate planned work
Present solutions, concepts, and results to internal and external clients
Create technical documentation

Requirements

What you’ll need

At least 5+ years of Data engineering experience, including the last 3 years building data processing
Practical experience in ML-based production recommendation systems
At least 5+ years of experience developing production-ready Python code, such as microservices and APIs
At least 3+ years of experience developing production-ready ML-related code
Practical experience with MLOps/LLMOps tools such as AzureML/AzureAI or GCP VertexAI
Practical experience with Databricks
Good understanding of ML/AI concepts, including algorithms, machine learning frameworks, model efficiency metrics, model life cycle, and AI architectures
Good understanding of cloud concepts and architectures, with working knowledge of selected cloud services, preferably Azure or GCP
Experience in at least one of: Data Warehouse, Data Lake, Data Integration, Data Governance, Machine Learning, Deep Learning, or MLOps
Practical experience with Spark/PySpark and Hive within Big Data Platforms such as Databricks, EMR, or similar
Experience designing and implementing data pipelines
Good communication skills
Ability to work in a team and support others
Responsibility for tasks and deliverables
Problem-solving skills and critical thinking
Fluency in written and spoken English

Benefits

Comp & perks

Stable employment with a company on the market since 2008
100% remote
Flexibility regarding working hours
Full-time position
Comprehensive online onboarding program with a “Buddy” from day 1
Cooperation with top-tier engineers and experts
Unlimited access to the Udemy learning platform from day 1
Certificate training programs
Upskilling support, capability development programs, Competency Centers, knowledge sharing sessions, community webinars, and 110+ training opportunities yearly
Opportunities for internal career growth
Diverse, inclusive, and values-driven community
Autonomy to choose the way you work
Referral bonuses
Activities to support well-being and health
Opportunities to donate to charities and support the environment