Job description

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!

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