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Staff Machine Learning Engineer India Jobs

4 Job Offers

Staff Machine Learning Engineer
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Join Uber’s Applied AI team in Bangalore as a Staff Machine Learning Engineer. Lead high-impact projects in generative AI, deep learning, and ML systems design. You’ll architect scalable solutions, influence technical direction, and collaborate across product teams. Ideal for experts with 10+ yea...
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India , Bangalore
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Not provided
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Uber
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Until further notice
Staff Machine Learning Engineer
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Join Uber Eats as a Staff Machine Learning Engineer in Bangalore, leading search ranking innovation. You will drive relevance and ranking improvements for millions of global users, leveraging 9+ years of ML expertise and strong system design skills. This tech lead role involves setting technical ...
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India , Bangalore
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Not provided
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Uber
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Until further notice
Staff Machine Learning Engineer
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Join our team in Bengaluru as a Staff Machine Learning Engineer. You will leverage your deep expertise in AWS MLOps, including SageMaker, S3, and CloudFormation, to deploy and manage production models. This role demands significant experience in Machine Learning Engineering to drive impactful pro...
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India , Bengaluru
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Not provided
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Bazaarvoice
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Until further notice
Staff Machine Learning Engineer
Save Icon
Location Icon
Location
India , Bengaluru
Salary Icon
Salary
Not provided
bazaarvoice.com Logo
Bazaarvoice
Expiration Date
Until further notice

About the Staff Machine Learning Engineer role

Explore the pinnacle of applied artificial intelligence by searching for Staff Machine Learning Engineer jobs. This senior-level role represents a critical fusion of advanced machine learning expertise, robust software engineering principles, and strategic leadership. Professionals in these positions are responsible for architecting, building, and maintaining the sophisticated ML systems that drive core business functions and innovative products. Unlike roles focused solely on research or experimentation, a Staff Machine Learning Engineer ensures that complex models are scalable, reliable, and efficiently integrated into production environments, delivering tangible value.

The core responsibilities of a Staff Machine Learning Engineer are multifaceted. Typically, they involve designing and implementing the underlying data and ML infrastructure that enables the deployment of models at scale. This includes creating robust data pipelines, developing model serving architectures, and establishing comprehensive monitoring for performance and drift. A significant part of the role is setting technical direction and defining best practices for ML engineering across the organization. Staff MLEs provide technical leadership, mentor senior and junior engineers, and drive cross-team initiatives to solve systemic challenges. They are expected to proactively identify technical debt, advocate for architectural improvements, and align the ML roadmap with long-term business objectives.

To succeed in Staff Machine Learning Engineer jobs, candidates must possess a deep and balanced skill set. A strong foundation in computer science, algorithms, and data structures is essential, coupled with extensive experience in machine learning frameworks and cloud platforms. Proficiency in languages like Python, along with expertise in distributed computing and large-scale data processing tools, is standard. Beyond technical prowess, the role demands exceptional soft skills. Strategic thinking, excellent communication, and the ability to translate complex technical concepts for stakeholders and executives are crucial. Leadership experience is paramount, as these engineers guide projects, influence organizational standards, and foster a culture of excellence in ML operations.

Ultimately, professionals pursuing Staff Machine Learning Engineer jobs are seasoned practitioners who bridge the gap between cutting-edge AI research and enterprise-grade software systems. They are pivotal in transitioning prototypes into powerful, reliable services that can handle real-world demands. If you are a leader passionate about shaping the future of AI implementation and driving technological evolution, exploring opportunities in this field offers a challenging and impactful career path at the forefront of innovation.