AI / ML Engineer (Remote)

<div><span><h2>Job Title: AI/ML Engineer</h2><h3>Job Summary</h3><div>We are seeking a highly skilled <strong>AI/ML Engineer</strong> to design, develop, and deploy scalable machine learning and deep learning solutions. The ideal candidate will have strong experience in <strong>computer vision</strong>, <strong>deep learning frameworks</strong>, and <strong>cloud-based ML deployment</strong>, along with solid <strong>software engineering and MLOps practices</strong>. You will work closely with cross-functional teams to build production-ready AI systems that deliver real business impact.</div><div><br></div><div>Experience: 5+ Years</div><div>Location: Bangalore</div><div>Timings: 2:30 to 11:30 PM IST</div><hr><h3>Key Responsibilities</h3><ul><li>Design, develop, and optimize <strong>machine learning and deep learning models</strong> using <strong>PyTorch</strong>.</li><li>Build and deploy <strong>computer vision solutions</strong> for real-world use cases.</li><li>Develop end-to-end <strong>ML pipelines</strong>, including data ingestion, preprocessing, training, validation, and deployment.</li><li>Implement and maintain <strong>MLOps workflows</strong> for model versioning, monitoring, CI/CD, and retraining.</li><li>Deploy and scale ML models on <strong>AWS cloud infrastructure</strong>.</li><li>Work with large-scale datasets using <strong>Databricks</strong> and distributed computing frameworks.</li><li>Collaborate with data scientists, product managers, and software engineers to translate business requirements into AI solutions.</li><li>Ensure high code quality by following <strong>software engineering best practices</strong> (modular design, testing, documentation).</li><li>Monitor model performance in production and continuously improve accuracy, efficiency, and reliability.</li></ul><hr><h3>Required Skills &amp; Qualifications</h3><ul><li>Strong proficiency in <strong>Python</strong> for machine learning and software development.</li><li>Hands-on experience with <strong>PyTorch</strong> for deep learning model development.</li><li>Solid understanding of <strong>deep learning architectures</strong> (CNNs, transfer learning, etc.).</li><li>Practical experience in <strong>computer vision</strong> applications.</li><li>Experience working with <strong>Databricks</strong> and large-scale data processing.</li><li>Strong knowledge of <strong>AWS services</strong> for ML deployment (EC2, S3, SageMaker, etc.).</li><li>Experience with <strong>MLOps tools and practices</strong> (model deployment, monitoring, CI/CD).</li><li>Good understanding of <strong>software engineering principles</strong> and production-grade system design.</li></ul><hr><h3>Preferred Qualifications</h3><ul><li>Experience deploying ML models in <strong>production environments</strong>.</li><li>Familiarity with containerization tools such as <strong>Docker</strong> and orchestration platforms like <strong>Kubernetes</strong>.</li><li>Exposure to real-time or batch inference systems.</li><li>Experience working in agile or fast-paced development environments.</li></ul><hr><h3>Nice to Have</h3><ul><li>Experience with optimization and performance tuning of ML models.</li><li>Knowledge of data security and compliance in cloud environments.</li><li>Experience with monitoring tools for ML model performance and drift detection.</li></ul></span></div>