AI Engineer
Indexed description
- Design, develop, train, and deploy AI and Machine Learning models to solve real-world business problems.
- Build intelligent AI solutions including:
- Predictive Analytics
- Classification Models
- Recommendation Systems
- Intelligent Automation
- Decision Support Systems
- Apply supervised and unsupervised machine learning techniques based on business requirements.
- Evaluate, validate, and optimize AI models to improve accuracy, robustness, scalability, and business value.
- Work with structured and unstructured datasets to prepare data for AI model training, validation, and inference.
- Design and optimize data pipelines supporting AI and machine learning workflows.
- Perform feature engineering, data transformation, cleansing, and validation activities.
- Utilize Python, SQL, NumPy, Pandas, and related libraries to process and analyze large-scale datasets.
- Deploy AI models using REST APIs, microservices, and cloud-native deployment architectures.
- Develop scalable model-serving APIs using Flask, FastAPI, or similar frameworks.
- Utilize Docker and CI/CD pipelines to enable automated, secure, and repeatable AI deployments.
- Ensure deployed AI solutions meet enterprise standards for scalability, reliability, performance, security, and maintainability.
- Monitor model performance, prediction quality, model drift, data quality, and retraining requirements.
- Troubleshoot production issues related to AI models, inference services, APIs, and data pipelines.
- Document AI models, technical designs, assumptions, experiments, and deployment procedures.
- Apply Responsible AI principles including fairness, explainability, bias mitigation, governance, and ethical AI practices.
- Collaborate with Product Managers, Data Engineers, Software Engineers, Data Scientists, and Business Stakeholders to deliver enterprise AI solutions.
- Translate complex business requirements into scalable AI-driven applications and intelligent automation solutions.
- Participate in Agile ceremonies, architecture discussions, code reviews, and continuous improvement initiatives.
- Stay updated with emerging technologies in Artificial Intelligence, Machine Learning, Generative AI, and Cloud Computing.
- 3+ years of experience in Artificial Intelligence, Machine Learning, Applied AI, or AI Engineering.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.
- Strong programming expertise in:
- Python (Mandatory)
- SQL
- Exposure to Java, C++, or Scala is an added advantage.
- Strong understanding of:
- Supervised Learning
- Unsupervised Learning
- Feature Engineering
- Model Evaluation
- Model Validation
- Predictive Analytics
- Hands-on experience with Deep Learning frameworks including:
- TensorFlow
- PyTorch
- Keras
- Strong expertise working with:
- NumPy
- Pandas
- SQL
- Structured and Unstructured Data
- Experience building and deploying production-grade AI and Machine Learning solutions.
- Experience developing REST APIs and model-serving applications using:
- Flask
- FastAPI
- Hands-on experience with:
- Docker
- Microservices Architecture
- CI/CD Pipelines
- Git Version Control
- Experience working with cloud platforms including:
- Microsoft Azure
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- Azure Machine Learning
- AWS SageMaker
- Strong analytical thinking, debugging, and problem-solving capabilities.
- Excellent communication, stakeholder management, and collaboration skills.
- Ability to convert business challenges into scalable AI-powered solutions.
- Strong ownership mindset with focus on quality, security, scalability, and continuous improvement.
- Experience with:
- Large Language Models (LLMs)
- Generative AI
- Natural Language Processing (NLP)
- Computer Vision
- Hands-on experience with MLOps platforms including:
- MLflow
- Kubeflow
- Apache Airflow
- Azure Machine Learning
- AWS SageMaker
- Familiarity with Big Data technologies including:
- Apache Spark
- Hadoop
- Understanding of:
- Responsible AI
- AI Ethics
- Bias Detection
- Explainable AI (XAI)
- AI Governance
- Experience deploying scalable cloud-native AI services using containerized and microservices architectures.
- Experience working in Agile and Scrum delivery environments.
- Domain experience within Manufacturing, Automotive, Supply Chain, Quality Engineering, Financial Services, Healthcare, or Enterprise Analytics is highly preferred.
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.
Join our passionate team and tailor your growth with us!
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