Job Description
Overview:
We are seeking a highly skilled and innovative AI / Machine Learning Engineer to design, develop, and deploy machine learning models and AI-driven solutions that solve complex business problems. This role focuses on building scalable ML systems, training predictive models, and integrating AI capabilities into production environments.
The AI/ML Engineer works closely with Data Scientists, Software Engineers, Product Teams, and Data Engineers to turn data into intelligent, production-ready systems.
Key Responsibilities:
- Machine Learning Model Development
- Design, build, and train machine learning and deep learning models
- Develop predictive, classification, recommendation, and NLP models
- Perform feature engineering, data preprocessing, and dataset optimization
- Evaluate model performance using appropriate metrics (accuracy, precision, recall, F1, AUC, etc.)
- Fine-tune hyperparameters to improve model performance and efficiency
AI System Development & Deployment (MLOps)
- Deploy machine learning models into production environments
- Build scalable ML pipelines and automated workflows
- Implement model monitoring, versioning, and retraining systems
- Integrate AI models into APIs, web apps, or enterprise systems
- Optimize models for speed, scalability, and cost efficiency
Data Handling & Engineering Collaboration
- Work with structured and unstructured datasets (text, images, audio, video)
- Collaborate with data engineers to build clean, reliable data pipelines
- Ensure data quality, integrity, and preprocessing standards
- Explore large datasets to extract patterns and insights
Research & Innovation
- Research and implement state-of-the-art AI/ML algorithms
- Experiment with deep learning frameworks (CNNs, RNNs, Transformers, LLMs)
- Stay updated with advancements in generative AI and large language models
- Prototype AI solutions for business use cases
Collaboration & Communication
- Work closely with product managers and stakeholders to define AI solutions
- Translate business problems into machine learning solutions
- Communicate model performance and technical insights clearly
- Support cross-functional teams in AI adoption
Requirements:
- Bachelor's or Master's degree in Computer Science, Data Science, AI, Mathematics, or related field
- Strong knowledge of machine learning algorithms and statistical modeling
- Proficiency in Python and ML libraries (Scikit-learn, TensorFlow, PyTorch)
- Experience with data processing tools (Pandas, NumPy, SQL)
- Understanding of model deployment and MLOps concepts
- Strong problem-solving and analytical skills
- Experience working with large datasets
- Preferred (Nice-to-Have):
- Experience with deep learning, NLP, computer vision, or generative AI
- Familiarity with cloud platforms (AWS, Azure, GCP)
- Experience with Docker, Kubernetes, and CI/CD pipelines
- Experience building LLM-based applications (GPT, BERT, LLaMA, etc.)
- Knowledge of data engineering tools (Spark, Hadoop)
- Contributions to open-source AI projects or research papers
Reporting To:
- Head of Data Science / AI Lead / Engineering Manager / CTO
- Employment Type & Work Setup:
- Full-time / Contract-based
- Onsite / Hybrid / Remote (depending on company structure)
- Tech-driven environments (startups, enterprise AI teams, SaaS companies)
- Flexible hours in agile development teams
- Work Environment & Conditions:
- Software engineering and data-driven development environment
- Agile, sprint-based product teams
- High collaboration with engineering, product, and analytics teams
- Focus on innovation, experimentation, and production scalability
- Fast-paced, research-driven technical environment