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.