▷ 3 Days Left: Machine Learning Engineer

3 weeks ago

Jamnagar, India Hyrfast Full time

Engagement Type: Contractual (Immediate Joiners Preferred) Location: Noida / Gurgaon / Indore / Bangalore / Pune / Remote (Hybrid model for on-site locations) About the Role We’re seeking experienced Machine Learning Engineers to join our client’s high-impact AI/ML projects. You’ll work on designing, developing, and deploying scalable ML solutions across domains — driving innovation, automation, and data-driven decision-making. Key Responsibilities - Design, develop, and implement end-to-end ML pipelines including data ingestion, feature engineering, and model deployment. - Collaborate with business, data, and product teams to deliver actionable insights and AI-driven solutions. - Build scalable data pipelines using PySpark and integrate ML models into production environments. - Develop and fine-tune models for forecasting, NLP, image/video analytics, and other advanced ML use cases. - Perform exploratory data analysis, model performance evaluation, and hyperparameter tuning. - Implement MLOps best practices for model lifecycle management, versioning, monitoring, and CI/CD automation. - Leverage AWS services such as Sagemaker, Bedrock, and Kendra for model training and deployment. - Encourage a culture of continuous learning, experimentation, and innovation within the team. Required Skills & Experience - Strong programming expertise in Python. - 3–10 years of hands-on experience in data/feature pipelines using PySpark. - Proficiency in ML model lifecycle, from data prep to production deployment. - Strong foundation in statistics and probability (hypothesis testing, distributions, regression, etc.). - Working knowledge of MLOps tools and frameworks for scalable deployments. - Exposure to AWS Cloud (Sagemaker, Bedrock, Kendra) and related services. - Familiarity with technical architecture, model management, and operational best practices. Good to Have - Experience with Generative AI and LLMs (LangChain, LlamaIndex, Foundation Model Tuning, Data Augmentation). - Experience with Docker and Kubernetes for containerized deployments. - Hands-on exposure to time-series modeling, forecasting, and advanced analytics. Who Should Apply - Professionals passionate about solving complex problems using AI/ML. - Engineers available for immediate or near-term joining. - Candidates open to contractual/consulting engagements with leading enterprise clients.

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