Machine Learning Engineer

🕒 May 27

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Shuru

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2021

🤖 Artificial Intelligence

🤝 B2B

🏢 Enterprise

Artificial Intelligence • B2B • Enterprise

Shuru is a product, AI, and technology consulting firm that partners with businesses to deliver strategic consulting, full-cycle product and custom software development, and curated engineering team extension. Their AI-native engineering teams build scalable AI applications, data engineering and analytics, cloud/DevOps, and API integrations to modernize systems and accelerate product delivery. Shuru operates globally with a remote-first model and emphasizes high ownership, design thinking, and measurable outcomes for enterprise and startup clients.

📋 Description

• Work with stakeholders to define machine learning solution designs based on cloud services such as Azure and Snowflake. • Design, build, and maintain machine learning pipelines and frameworks to support enterprise analytics, reporting, and product needs. • Collaborate with data science, ML engineering, data quality, and product teams on model deployment architecture and implementation. • Manage, configure, and optimize cloud environments and related machine learning services. • Implement tools and processes for model integration, storage, profiling, monitoring, processing, management, and archival. • Support enterprise-wide model governance, performance tracking, and lifecycle management standards. • Recommend improvements to ML platforms, tools, and development practices to support strategic technology and business objectives. • Work with SaaS vendors and strategic partners to implement and maintain modern machine learning solutions. • Use Agile practices to manage delivery, contribute to project planning, and support successful rollout of ML products. • Partner with internal stakeholders to understand business requirements and translate them into reliable ML operations solutions. • Stay current with emerging MLOps tools, cloud technologies, and best practices to ensure solutions remain scalable, secure, and fit for purpose.

🎯 Requirements

• Bachelor's degree in Computer Science, Engineering or Technical Field preferred. • Minimum 3-7 years of relevant experience. • Proven experience in machine learning engineering and operations. • Profound understanding of machine learning concepts, model lifecycle management, and experience in model management capabilities including model definitions, performance management and integration. • Execution of model deployment, monitoring, profiling, governance and analysis initiatives. • Excellent interpersonal, oral, and written communication; Ability to relate ideas and concepts to others; write reports, business correspondence, project plans and procedure documents. • Solid Python, ML frameworks (e.g., TensorFlow, PyTorch), data modeling, and programming skills. • Experience and strong understanding of cloud architecture and design (AWS, Azure, GCP). • Experience using modern approaches to automating machine learning pipelines. • Agile and Waterfall methodologies. • Ability to work independently and manage multiple task assignments within a structured implementation methodology. • Personally invested in continuous improvement and innovation. • Motivated, self-directed individual that works well with minimal supervision. • Must have experience working across multiple teams/technologies. • Preferred but not essential: Experience with business intelligence tools (preferably PowerBI). • Preferred but not essential: Experience with MLOps tools (e.g., MLflow, Kubeflow).

🏖️ Benefits

• Work on global projects with clients from worldwide. • Be part of a remote-first culture-work from anywhere with flexibility. • Enjoy team-building activities and regular outings. • Collaborate and grow in a supportive environment with opportunities to learn from senior engineers. • Competitive salary and benefits package.