... Data & ML Platform using Databricks as the foundational technology. Remote - candidate can be ... This role focuses on building platform capabilities that enable federated domain teams across R&D ...
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... Data & ML Platform using Databricks as the foundational technology. Remote - candidate can be ... This role focuses on building platform capabilities that enable federated domain teams across R&D ...
Senior AI Product Manager
Ames, IA · On-site +1
$123K - $163K/yr
Conduct in-depth market research, competitive analysis, and customer discovery to identify unmet ... Lead the end-to-end product lifecycle for AI/ML features, from ideation and validation to ...
Senior AI Product Manager
Ames, IA · On-site +1
$123K - $163K/yr
Conduct in-depth market research, competitive analysis, and customer discovery to identify unmet ... Lead the end-to-end product lifecycle for AI/ML features, from ideation and validation to ...
... ML, Cloud, Privacy & Compliance, Security, Incident Response, and the C-suite. * Identify, research ... Remote
... ML, Cloud, Privacy & Compliance, Security, Incident Response, and the C-suite. * Identify, research ... Remote
Remote Ml Researcher information
What are some common challenges faced by remote ML researchers and how can they overcome them?
Remote ML researchers often encounter challenges such as limited real-time collaboration, managing large datasets remotely, and ensuring consistent communication with their teams. Overcoming these obstacles typically involves leveraging collaboration tools (like Slack, GitHub, and Zoom), setting up efficient remote access to computational resources, and establishing regular check-ins with colleagues. Building a proactive communication routine and sharing progress updates can help maintain team alignment and foster a sense of connection, even when working from different locations.
What is a remote ML researcher?
Remote ML Researchers are professionals who specialize in machine learning (ML) and conduct their research while working outside of a traditional office environment, often from home or other remote locations. They design, implement, and evaluate algorithms, models, and systems to solve complex data problems, collaborating virtually with teams and stakeholders. Their work can span industries like technology, healthcare, finance, and more, and typically involves tasks such as data analysis, model development, and publishing research findings. Remote ML Researchers rely heavily on digital communication tools and cloud-based platforms to share ideas, code, and results.
What are the key skills and qualifications needed to thrive as a remote ML researcher, and why are they important?
To thrive as a Remote ML Researcher, you need a strong background in machine learning theory, programming (Python, TensorFlow, PyTorch), and a relevant degree such as computer science or statistics. Familiarity with cloud computing platforms, distributed systems, version control (Git), and experience publishing in peer-reviewed journals are commonly required. Excellent problem-solving skills, self-motivation, and effective written communication are crucial for collaborating remotely and sharing findings. These skills ensure high-quality research output, successful collaboration in distributed teams, and ongoing advancement in the fast-evolving field of machine learning.
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Corteva Agriscience rating
8.3
Based on 75 frontline employees who took The Breakroom Quiz
50th of 538 rated manufacturers
Job description
Platform Staffing Group (an STA Group Company) is looking for a Sr. Principal Software Architect to assist our client in leading the development and evolution of our Data & ML Platform using Databricks as the foundational technology.
Remote - candidate can be considered remote if currently lives in the US and lives more than 50 miles from Johnston, IA location. Johnston, IA – candidate living within 50-mile radius of location required onsite T/W/TH each week.
DUTIES & RESPONSIBILITIES
This individual will lead the development and evolution of our client’s Data & ML Platform using Databricks as the foundational technology. This role focuses on building platform capabilities that enable federated domain teams across R&D to efficiently build, operate, and manage their own data and AI products. This includes working closely with data professionals to understand friction points and develop platform features, patterns, and enablement pathways that improve productivity, governance, and adoption. This work directly supports a federated data mesh strategy and is expected to grow over multiple years.
Develop and enhance Databricks-based platform capabilities to improve the productivity, governance, and autonomy of federated domain teams.
Collaborate with Data Platform and ML Platform leadership to align platform features to strategic roadmap and domain enablement needs.
Act as a technical and architectural advisor to teams onboarding to the platform, helping them apply best practices rather than building their solutions for them.
Identify friction points experienced by data engineers, data scientists, and analysts, and translate them into platform features, reusable patterns, and enablement artifacts.
Work across federated data domains to ensure platform consistency, governance alignment, and scalable adoption aligned with data mesh principles.
Provide technical leadership while still being capable of hands-on development when shaping reference implementations, IaC modules, or platform accelerators.
Advocate for secure-by-default design, applying modern security principles and working knowledge of cyber practices in a cloud-native platform context.
Contribute to FinOps-aware decision-making by communicating trade-offs between different Databricks implementation patterns (clusters vs. serverless vs. SQL warehouses, Unity Catalog configuration, etc.).
Required Skills
7+ years of technical leadership with data or platform engineering roles preferred
Experience or deep understanding of designing or enabling federated data/ML environments where teams self-serve platform capabilities.
Strong understanding of platform architecture and patterns that support data mesh or domain-oriented enablement.
Ability to think in terms of platform products including prioritizing reusable capabilities, reducing cognitive load for users, and avoiding central engineering bottlenecks.
Experience influencing architecture decisions and guiding teams through platform-aligned adoption pathways.
Knowledge of/or expertise with Databricks as a platform beyond notebook usage, including governance, workspace design, multi-domain enablement, and Unity Catalog patterns.
Nice to Have Skills
Hands-on familiarity with Terraform, AWS infrastructure concepts (IAM, S3, networking), and IaC workflows.
Platform mindset with experience building internal platform products with developer experience and scale in mind.
General knowledge of cybersecurity and secure-by-default design patterns in cloud platforms.
Awareness of FinOps principles and cost optimization patterns specific to Databricks (e.g., cluster policy trade-offs, compute model selection, multi-workspace vs multi-catalog trade-offs).
Experience working within a federated data governance or data mesh operating model.
PLATFORM STAFFING GROUP, an STA Group Company IS AN EQUAL OPPORTUNITY EMPLOYER Follow us on X @PLATSTAFFJOBS
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Benefits
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About Corteva
Sourced by ZipRecruiter
Industry
Manufacturing
Company size
10,000+ Employees
Headquarters location
Indianapolis, IN, US
Year founded
2018