The Role
Design, develop, and deploy production-grade ML solutions and Digital Twin models for smart manufacturing. Build predictive/prescriptive models (predictive maintenance, anomaly detection, throughput, scheduling), create feature and streaming pipelines, implement MLOps (training/deployment, model registry, drift monitoring), collaborate with engineers and SMEs, support plant visits, and ensure scalable, monitored AI solutions for industrial operations.
Summary Generated by Built In
What You ‘ll Do
You will join our high performance Data & AI team and play a key role in building next-generation AI-powered Digital Twin solutions that enable smart manufacturing, Industry 4.0/5.0 transformation, and intelligent factory operations.
- Design, develop, and deploy machine learning solutions that solve complex manufacturing and industrial business problems.
- Build predictive and prescriptive machine learning models for manufacturing operations and production optimization.
- Develop AI models for:
- Predictive Maintenance
- Predictive Quality
- Anomaly Detection
- Root Cause Analysis
- Throughput Prediction
- Cycle Time Prediction
- Capacity Prediction
- Production Scheduling Optimization
- Operator Assistance Recommendations
- Develop intelligent Digital Twin models across:
- Station Twin
- Product Twin (SFC)
- Line Twin
- Warehouse Twin
- Build AI capabilities supporting:
- Process Deviation Detection
- Robot Behavior Prediction
- Conveyor Congestion Prediction
- Torque Anomaly Detection
- Vision Inspection Optimization
- Remaining Process Time Estimation
- Yield Prediction
- Simulation Calibration
- Design and develop feature engineering pipelines, scalable training datasets, and streaming data transformation workflows.
- Build and maintain real-time machine learning pipelines using operational technology (OT) telemetry, IIoT devices, and streaming platforms.
- Collaborate with Product Architects, Manufacturing SMEs, Software Engineers, and Data Engineers to deliver enterprise-grade AI solutions.
- Build and maintain MLOps capabilities including:
- Model Training Pipelines
- Model Deployment Pipelines
- Model Registry
- Feature Store
- Drift Monitoring
- Experiment Tracking
- Automated Retraining Workflows
- CI/CD for Machine Learning
- Work with structured, unstructured, time-series, and streaming datasets to develop scalable AI solutions.
- Ensure production-ready deployment, monitoring, scalability, and continuous improvement of AI models.
- Support digital transformation initiatives across manufacturing plants through intelligent automation and advanced analytics.
- Participate in plant visits to understand manufacturing operations, industrial workflows, and operational challenges.
What We Seek In You
- 3 to 5 years of experience in Machine Learning Engineering, Applied AI, Data Science, or AI Engineering.
- Strong programming expertise in:
- Python
- SQL
- Exposure to Go programming is an added advantage.
- Strong hands-on experience developing machine learning models using:
- Scikit-learn
- XGBoost
- LightGBM
- PyTorch or TensorFlow
- Strong understanding of:
- Time Series Forecasting
- Classification
- Regression
- Clustering
- Anomaly Detection
- Feature Engineering
- Model Evaluation
- Hyperparameter Tuning
- Experience building production-grade MLOps solutions using one or more of:
- MLflow
- Azure Machine Learning
- Kubeflow
- SageMaker
- Databricks ML
- Vertex AI
- Strong understanding of:
- Model Registry
- Experiment Tracking
- Model Deployment
- Drift Monitoring
- Feature Store
- Experience working with enterprise data platforms including:
- PostgreSQL
- Kafka
- Azure Data Lake Storage (ADLS)
- Azure Blob Storage
- Delta Lake
- Spark (Preferred)
- TimescaleDB
- Exposure to Microsoft Azure cloud services including:
- Azure Machine Learning
- Azure Kubernetes Service (AKS)
- Azure Data Lake
- Experience working with real-time streaming data and industrial telemetry pipelines.
- Exposure to visualization frameworks such as:
- Plotly
- Streamlit
- Dash
- Grafana
- Familiarity with modern AI frameworks including:
- LangChain
- LangGraph
- Ray
- Vector Databases
- Large Language Model (LLM) APIs
- Strong understanding of Digital Twin concepts, Industrial AI, and intelligent manufacturing systems.
- Experience working in one or more of the following domains:
- Manufacturing
- Industrial Automation
- Smart Factory
- Industrial IoT (IIoT)
- Robotics
- Supply Chain Analytics
- Quality Engineering
- Exposure to:
- OPC-UA
- MQTT
- PLC Signals
- Digital Twin Platforms
- Time Series Analytics
- Simulation Models
- Industry 4.0 / Industry 5.0
- Computer Vision for Manufacturing
- Strong analytical thinking, problem-solving, and debugging capabilities.
- Ability to work with large-scale real-time streaming datasets and production AI systems.
- Excellent communication, stakeholder management, and documentation skills.
- Strong ownership mindset with the ability to deliver production-ready AI solutions.
- Willingness to travel to manufacturing plants for business understanding and solution validation.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Electronics, or a related Engineering discipline.
Life At Next
At our core, we're driven by the mission of tailoring growth for our customers by enabling them to transform their aspirations into tangible outcomes. We're dedicated to empowering them to shape their futures and achieve ambitious goals. To fulfil this commitment, we foster a culture defined by agility, innovation, and an unwavering commitment to progress. Our organizational framework is both streamlined and vibrant, characterized by a hands-on leadership style that prioritizes results and fosters growth.
Perks Of Working With Us
- Clear objectives to ensure alignment with our mission, fostering your meaningful contribution.
- Abundant opportunities for engagement with customers, product managers, and leadership.
- You'll be guided by progressive paths while receiving insightful guidance from managers through ongoing feedforward sessions.
- Cultivate and leverage robust connections within diverse communities of interest. Choose your mentor to navigate your current endeavors and steer your future trajectory.
- Embrace continuous learning and upskilling opportunities through Nexversity.
- Enjoy the flexibility to explore various functions, develop new skills, and adapt to emerging technologies. Embrace a hybrid work model promoting work-life balance.
- Access comprehensive family health insurance coverage, prioritizing the well-being of your loved ones.
- Embark on accelerated career paths to actualize your professional aspirations.
Who we are?
We enable high growth enterprises build hyper personalized solutions to transform their vision into reality. With a keen eye for detail, we apply creativity, embrace new technology and harness the power of data and AI to co-create solutions tailored made to meet unique needs for our customers.
Join our passionate team and tailor your growth with us!
Skills Required
- 3 to 5 years of experience in Machine Learning Engineering, Applied AI, Data Science, or AI Engineering.
- Proficiency in Python
- Proficiency in SQL
- Exposure to Go programming
- Hands-on experience with Scikit-learn
- Hands-on experience with XGBoost
- Hands-on experience with LightGBM
- Hands-on experience with PyTorch or TensorFlow
- Strong understanding of time series forecasting, classification, regression, clustering, anomaly detection, feature engineering, model evaluation, and hyperparameter tuning
- Experience building production-grade MLOps solutions using one or more of MLflow, Azure Machine Learning, Kubeflow, SageMaker, Databricks ML, Vertex AI
- Understanding of model registry, experiment tracking, model deployment, drift monitoring, feature store
- Experience with enterprise data platforms such as PostgreSQL, Kafka, Azure Data Lake Storage, Azure Blob Storage, Delta Lake, TimescaleDB
- Experience working with real-time streaming data and industrial telemetry pipelines
- Exposure to Microsoft Azure cloud services including Azure Machine Learning, AKS, Azure Data Lake
- Familiarity with visualization frameworks such as Plotly, Streamlit, Dash, Grafana
- Familiarity with modern AI frameworks including LangChain, LangGraph, Ray, Vector Databases, and LLM APIs
- Strong understanding of Digital Twin concepts, Industrial AI, and intelligent manufacturing systems
- Experience in one or more domains: Manufacturing, Industrial Automation, Smart Factory, IIoT, Robotics, Supply Chain Analytics, Quality Engineering
- Exposure to OPC-UA, MQTT, PLC signals, and Digital Twin platforms
- Experience with time series analytics and simulation calibration/models
- Strong analytical, communication, stakeholder management, and documentation skills
- Willingness to travel to manufacturing plants for business understanding and validation
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Electronics, or related engineering discipline
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The Company
What We Do
TVS Next is a digital technology and consulting company that accelerates growth for clients through digital transformation and enterprise modernization solutions, leveraging software engineering, intelligence, and experience design.
