Machine Learning Engineer

🕒 March 3

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Smart Working

51 - 200 employees

🤝 B2B

☁️ SaaS

🎯 Recruiter

B2B • SaaS • Recruitment

Smart Working is a recruitment service specializing in sourcing and providing top-tier software developers from around the world to meet the needs of businesses. With a robust vetting process that includes technical assessments and background checks, Smart Working ensures that clients receive highly skilled developers adept in various programming languages and frameworks. The company focuses on flexible and remote hiring solutions, allowing businesses to efficiently scale their development teams while benefiting from significant cost savings.

📋 Description

• Architect, implement, and maintain production-grade, low-latency ML services for ranking, recommendation, and forecasting use cases • Collaborate with data scientists, product managers, and engineers to identify the best technical approaches to product and infrastructure challenges • Design and support experimentation frameworks to test hypotheses and measure improvements to models • Advise on data strategy, ensuring high-quality, well-structured datasets are available for current and future data science initiatives • Deliver machine learning models that meet agreed engineering standards, ensuring scalability, resilience, and long-term maintainability • Enhance and evolve an AWS-native MLOps platform, supporting high availability and low-latency inference • Monitor, maintain, and continuously improve deployed models in production environments • Contribute positively to team culture, demonstrating curiosity, ownership, and a bias toward learning and improvement

🎯 Requirements

• 5+ years of total professional experience, operating at a senior engineering level • 3+ years of hands-on experience in Machine Learning, including taking models from experimentation to production • 3+ years of experience with Python, writing production-quality, maintainable code • 3+ years of experience working with SQL in analytical or data-intensive environments • Strong experience building and operating production ML systems, including model serving and monitoring • Solid understanding of experimentation, model evaluation, and performance trade-offs in real-world systems • Experience working closely with cross-functional teams in a collaborative, product-focused environment • Strong engineering mindset, with a focus on scalability, reliability, and future-proof solutions

🏖️ Benefits

• Fixed Shifts: 12:00 PM - 9:30 PM IST (Summer) | 1:00 PM - 10:30 PM IST (Winter) • No Weekend Work: Real work-life balance, not just words • Day 1 Benefits: Laptop and full medical insurance provided • Support That Matters:Mentorship, community, and forums where ideas are shared • True Belonging: A long-term career where your contributions are valued

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