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.
Summary
Build and operate production machine learning systems with data science teams, implementing ML and LLM automation, industrialized pipelines, and MLOps/LLMOps frameworks. Requires 5+ years in data engineering and production Python including 3+ years in production ML code, plus Databricks, Spark/PySpark, and Azure or GCP.
Responsibilities
Implement ML models into production; Implement LLM/ML/AI automation for scale; Design, deliver and manage processing pipelines; Define ML lifecycle and MLOps/LLMOps best practices; Gather requirements and present solutions; Create technical documentation
Qualifications
Practical experience in ML-based production recommendation systems; Practical experience in MLOps/LLMOps tools like AzureML/AzureAI or GCP VertexAI; Practical experience with Databricks; Good understanding of ML/AI and Cloud concepts; Practical experience in Spark/PySpark and Hive
Experience requirements
At least 5+ years of Data engineering experience with last 3 years in building Data processing; At least 5+ years in production-ready Python code development; At least 3+ years in production-ready ML-related code development
Benefits
Flexibility regarding working hours; Unlimited access to Udemy learning platform; Certificate training programs; Upskilling support and training opportunities; Well-being and health activities