ML/AI Engineer - Classical ML

Role: ML/AI Engineer

Location: India, Remote

Lingaro Group is the end-to-end data services partner to global brands and enterprises. We lead our clients through their data journey, from strategy through development to operations and adoption, helping them to realize the full value of their data.

Since 2008, Lingaro has been recognized by clients and global research and advisory firms for innovation, technology excellence, and the consistent delivery of highest-quality data services. Our commitment to data excellence has created an environment that attracts the brightest global data talent to our team.

What You’ll Be Doing:

The person we are looking for will become part of Data Science and AI Competency Center working in AI Engineering team.

The key duties are:

• Working with Data Science teams to implement Machine Learning models into production
• Practical and innovative implementations of LLM/ML/AI automation, for scale and efficiency
• Design, delivery and management of industrialized processing pipelines
• Defining and implementing best practices in ML models life cycle and ML operations/LLM operations
• Implementing AI /MLOps/LLMOps frameworks and supporting Data Science teams in best practices
• Gathering and applying knowledge on modern techniques, tools and frameworks in the area of ML Architecture and Operations
• Gathering technical requirements & estimating planned work
• Presenting solutions, concepts and results to internal and external clients
• Creating technical documentation

What We’re Looking For:

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

We Offer:

• Stable employment. On the market since 2008, 1300+ talents currently on board in 7 global sites.
• 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. Lingarians earn 500+ technology certificates yearly.
• Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly.
• Grow as we grow as a company. 76% of our managers are internal promotions.
• A diverse, inclusive, and values-driven community.
• Autonomy to choose the way you work. We trust your ideas.
• Create our community together. Refer your friends to receive bonuses.
• Activities to support your well-being and health.
• Plenty of opportunities to donate to charities and support the environment.

Missing one or two of these qualifications? We still want to hear from you! If you bring a positive mindset, we’ll provide an environment where you feel valued and empowered to learn and grow.