RedyHire Technologies is an innovation-driven company reimagining the future of hiring. Founded in Bengaluru, we blend AI, data, and automation to solve the toughest recruitment challenges. Our mission is to make hiring efficient, unbiased, and deeply insightful for companies of all sizes. We’re a team of technologists, problem-solvers, and hiring experts building tools that matter. At RedyHire, we don’t just build software — we build smarter hiring ecosystems.

Machine Learning Engineer

Experience: 5 to 9 years

Key Skills: Strong Programming & ML Foundations, AWS Machine Learning Services (SageMaker + Ecosystem, Data Engineering & MLOps (Workflow, Deployment, and Monitoring)

No. of Open Position:1

Location: Bangalore / Kochi

Work Mode: Hybrid / Remote

Job Description

We are seeking a highly skilled and motivated Machine Learning Engineer with a strong

foundation in programming and machine learning, hands-on experience with AWS

Machine Learning services (especially SageMaker), and a solid understanding

of Data Engineering and MLOps practices. You will be responsible for designing,

developing, deploying, and maintaining scalable ML solutions in a cloud-native

environment.

Key Responsibilities:

• Design and implement machine learning models and pipelines using AWS

SageMaker and related services.

• Develop and maintain robust data pipelines for training and inference

workflows.

• Collaborate with data scientists, engineers, and product teams to translate

business requirements into ML solutions.

• Implement MLOps best practices including CI/CD for ML, model versioning,

monitoring, and retraining strategies.

• Optimize model performance and ensure scalability and reliability in production

environments.

• Monitor deployed models for drift, performance degradation, and anomalies.

• Document processes, architectures, and workflows for reproducibility and

compliance.

Required Skills & Qualifications:

• Strong programming skills in Python and familiarity with ML libraries (e.g., scikit-

learn, TensorFlow, PyTorch).

• Solid understanding of machine learning algorithms, model evaluation, and

tuning.

• Hands-on experience with AWS ML services, especially SageMaker, S3,

Lambda, Step Functions, and CloudWatch.

• Experience with data engineering tools (e.g., Apache Airflow, Spark, Glue)

and workflow orchestration.

Machine Learning Engineer - Job Description

• Proficiency in MLOps tools and practices (e.g., MLflow, Kubeflow, CI/CD

pipelines, Docker, Kubernetes).

• Familiarity with monitoring tools and logging frameworks for ML systems.

• Excellent problem-solving and communication skills.

Preferred Qualifications:

• AWS Certification (e.g., AWS Certified Machine Learning – Specialty).

• Experience with real-time inference and streaming data.

• Knowledge of data governance, security, and compliance in ML systems.