Senior Fullstack AI/ML Engineer

About the Role

We are seeking a highly skilled Senior AI/ML Engineer to join our dynamic team. The ideal candidate will have extensive experience in designing, building, and deploying machine learning models and AI solutions to solve real-world business challenges. You will collaborate with cross-functional teams to create and integrate AI/ML models into end-to-end applications, ensuring models are accessible through APIs or product interfaces for real-time usage.

Responsibilities

• Lead the design, development, and deployment of machine learning models for various use cases such as recommendation systems, computer vision, natural language processing (NLP), and predictive analytics.

• Work with large datasets to build, train, and optimize models using techniques such as classification, regression, clustering, and neural networks.

• Fine-tune pre-trained models and develop custom models based on specific business needs.

• Collaborate with data engineers to build scalable data pipelines and ensure the smooth integration of models into production.

• Collaborate with frontend/backend engineers to build AI-driven features into products or platforms.

• Build proof-of-concept or production-grade AI applications and tools with intuitive UIs or workflows.

• Ensure scalability and performance of deployed AI solutions within the full application stack.

• Implement model monitoring and maintenance strategies to ensure performance, accuracy, and continuous improvement of deployed models.

• Design and implement APIs or services that expose machine learning models to frontend or other systems

• Utilize cloud platforms (AWS, GCP, Azure) to deploy, manage, and scale AI/ML solutions.

• Stay up-to-date with the latest advancements in AI/ML research, and apply innovative techniques to improve existing systems.

• Communicate effectively with stakeholders to understand business requirements and translate them into AI/ML-driven solutions.

• Document processes, methodologies, and results for future reference and reproducibility.

Required Skills & Qualifications

• Experience: 3-5+ years of experience in AI/ML engineering roles, with a proven track record of successfully delivering machine learning projects.

• AI/ML Expertise: Strong knowledge of machine learning algorithms (supervised, unsupervised, reinforcement learning) and AI techniques, including NLP, computer vision, and recommendation systems.

• Programming Languages: Proficient in Python and relevant ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras.

• Data Manipulation: Experience with data manipulation libraries such as Pandas, NumPy, and SQL for managing and processing large datasets.

• Model Development: Expertise in building, training, deploying, and fine-tuning machine learning models in production environments.

• Cloud Platforms: Experience with cloud platforms such as AWS, GCP, or Azure for the deployment and scaling of AI/ML models.

• MLOps: Knowledge of MLOps practices for model versioning, automation, and monitoring.

• Data Preprocessing: Proficient in data cleaning, feature engineering, and preparing datasets for model training.

• Strong experience building and deploying end-to-end AI-powered applications— not just models but full system integration.

• Hands-on experience with Flask, FastAPI, Django, or similar for building REST APIs for model serving.

• Understanding of system design and software architecture for integrating AI into production environments.

• Experience with frontend/backend integration (basic React/Next.js knowledge is a plus).

• Demonstrated projects where AI models were part of deployed user-facing applications.

• NLP & Computer Vision: Hands-on experience with natural language processing or computer vision projects.

• Big Data: Familiarity with big data tools and frameworks (e.g., Apache Spark, Hadoop) is an advantage.

• Problem-Solving Skills: Strong analytical and problem-solving abilities, with a focus on delivering practical AI/ML solutions.

Nice to Have

• Experience with deep learning architectures (CNNs, RNNs, GANs, etc.) and techniques.

• Knowledge of deployment strategies for AI models using APIs, Docker, or Kubernetes.

• Experience building full-stack applications powered by AI (e.g., chatbots, recommendation dashboards, AI assistants, etc.).

• Experience deploying AI/ML models in real-time environments using API gateways, microservices, or orchestration tools like Docker and Kubernetes.

• Solid understanding of statistics and probability.

• Experience working in Agile development environments.

What You'll Gain

• Be part of a forward-thinking team working on cutting-edge AI/ML technologies.

• Collaborate with a diverse, highly skilled team in a fast-paced environment.

• Opportunity to work on impactful projects with real-world applications.

• Competitive salary and career growth opportunities