The Role
Design, develop, deploy, and scale enterprise AI and machine learning solutions, including predictive models, recommendation engines, automation, and model-serving APIs. Build data pipelines and MLOps workflows, monitor model performance and drift, troubleshoot production systems, and implement responsible AI practices. Collaborate with technical and business stakeholders, contribute to architecture and code reviews, and mentor junior engineers while applying cloud-native technologies.
Summary Generated by Built In
What You'll Do
As a Senior AI Engineer, you will design, develop, deploy, and scale enterprise-grade AI and Machine Learning solutions that drive intelligent automation and business transformation.
- Design and develop end-to-end AI/ML solutions for real-world business problems.
- Build predictive models, classification systems, recommendation engines, and intelligent automation solutions.
- Apply supervised, unsupervised, and deep learning techniques based on business requirements.
- Develop and optimize data pipelines, feature engineering, and model training workflows.
- Evaluate and improve model accuracy, scalability, robustness, and business impact.
- Build and deploy scalable model-serving APIs using Python, FastAPI, Flask, or similar frameworks.
- Deploy AI solutions using Docker, microservices, CI/CD pipelines, and cloud-native architectures.
- Monitor model performance, data quality, model drift, and retraining requirements.
- Troubleshoot production issues across AI models, APIs, and data pipelines.
- Apply MLOps practices for model versioning, deployment, monitoring, and lifecycle management.
- Implement Responsible AI practices, including explainability, bias mitigation, governance, and security.
- Collaborate with Data Scientists, Data Engineers, Software Engineers, Product Managers, and business stakeholders.
- Mentor junior engineers and contribute to architecture, code reviews, and technical best practices.
- Stay current with emerging AI, Generative AI, LLM, and cloud technologies.
What We Seek In You
- 5–8 years of experience in AI Engineering, Machine Learning, Applied AI, or related fields.
- Strong hands-on expertise in Python and SQL.
- Machine Learning and Deep Learning
- Supervised and Unsupervised Learning
- Feature Engineering and Model Evaluation
- Model Optimization and Validation
- Hands-on experience with TensorFlow, PyTorch, Keras, Scikit-learn, NumPy, and Pandas.
- Experience building and deploying production-grade AI/ML applications.
- Strong experience with FastAPI, Flask, REST APIs, and Microservices.
- Hands-on experience with Docker, Git, CI/CD, and cloud-native deployments.
- Experience with at least one major cloud platform: Azure, AWS, or GCP.
- Experience with AI/ML platforms such as Azure Machine Learning, AWS SageMaker, or Vertex AI.
- Strong understanding of MLOps, model monitoring, model drift, and retraining workflows.
- Excellent problem-solving, debugging, communication, and stakeholder management skills.
- Ability to translate complex business challenges into scalable AI-powered solutions.
Preferred Qualifications
- Experience with Generative AI, Large Language Models (LLMs), RAG, and NLP.
- Exposure to Computer Vision and advanced AI use cases.
- Experience with MLOps tools such as MLflow, Kubeflow, or Apache Airflow.
- Familiarity with Apache Spark and Big Data technologies.
- Understanding of Responsible AI, Explainable AI (XAI), AI Governance, and AI Ethics.
- Experience designing scalable, secure, and cloud-native AI architectures.
- Experience in domains such as Manufacturing, Automotive, Supply Chain, Financial Services, Healthcare, or Enterprise Analytics.
Life at Next
At Next, we enable high-growth enterprises to transform their vision into reality through technology, data, and AI. We foster a culture of agility, innovation, continuous learning, and hands-on leadership.
Perks of Working With Us
- Clear career growth and accelerated learning opportunities.
- Exposure to customers, product leaders, and emerging technologies.
- Continuous learning and upskilling through Nexversity.
- Mentorship and opportunities to explore diverse technologies and functions.
- Hybrid work model supporting work-life balance.
- Comprehensive family health insurance.
- A collaborative environment focused on innovation, ownership, and growth.
Join our passionate team and tailor your growth with us!
Skills Required
- 5-8 years of experience in AI Engineering, Machine Learning, Applied AI, or related fields
- Strong hands-on expertise in Python and SQL
- Knowledge of machine learning, deep learning, supervised learning, unsupervised learning, feature engineering, model evaluation, optimization, and validation
- Hands-on experience with TensorFlow, PyTorch, Keras, Scikit-learn, NumPy, and Pandas
- Experience building and deploying production-grade AI/ML applications
- Strong experience with FastAPI, Flask, REST APIs, and microservices
- Hands-on experience with Docker, Git, CI/CD, and cloud-native deployments
- Experience with at least one major cloud platform: Azure, AWS, or GCP
- Experience with Azure Machine Learning, AWS SageMaker, or Vertex AI
- Strong understanding of MLOps, model monitoring, model drift, and retraining workflows
- Problem-solving, debugging, communication, and stakeholder management skills
- Ability to translate complex business challenges into scalable AI-powered solutions
- Experience with Generative AI, LLMs, RAG, and NLP
- Exposure to computer vision and advanced AI use cases
- Experience with MLflow, Kubeflow, or Apache Airflow
- Familiarity with Apache Spark and big data technologies
- Understanding of Responsible AI, Explainable AI, AI Governance, and AI Ethics
- Experience designing scalable, secure, and cloud-native AI architectures
- Experience in manufacturing, automotive, supply chain, financial services, healthcare, or enterprise analytics
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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.
