Data Analytics
Django
FlaskAbout 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
Shubham Vishwakarma
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