Senior Machine Learning Systems Engineer, Ads ML Experience Platform | JobSetuu

Description

Job Overview

• Source: Jobicy

Job Description

Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence

Team Overview

We are building the next generation of ML research tools and agentic AI platforms that power machine learning development across Reddit. Our mission is to accelerate the Ads ML lifecycle – from experimentation and training to deployment, evaluation, and autonomous operations – through scalable platform services, intelligent automation, and developer-centric tooling.

Our team owns critical platform capabilities including offline ML experimentation systems, production training orchestration frameworks, ML lifecycle automation and, agentic ML frameworks that enable faster model iterations.

We are looking for an experienced engineer with deep expertise in large-scale distributed systems, ML platforms, and emerging agentic architectures to help define and build the foundational tooling for the next generation of our machine learning devX tooling.

What You’ll Do

• Design and build large-scale offline ML experimentation platforms that enable reproducible research, model development, evaluation, and promotion workflows.
• Develop production-grade training orchestration frameworks supporting distributed training, hyperparameter optimization, model evaluation, and automated retraining.
• Build infrastructure for experiment tracking, metadata management, lineage, artifact versioning, model registries, and reproducibility.
• Partner with ML engineers and researchers to improve experimentation velocity and operational efficiency.
• Build automated workflows for model promotion, rollback, compliance validation, and continuous evaluation.
• Design and build an agentic AI execution platform supporting autonomous and human-in-the-loop workflows, including multi-agent orchestration, memory/context systems, and scalable workflow infrastructure.

What You Bring

• 5+ years in infrastructure/platform engineering or large-scale distributed systems.
• 2+ years of hands-on experience building and operating production ML infrastructure, developer SDKs, platform APIs, or self-service AI tooling.
• Experience building workflow orchestration systems, developer platforms, or large-scale automation frameworks.
• Experience with distributed data processing systems such as Spark, Flink, Ray, or equivalent technologies.
• Experience with modern orchestration and workflow technologies such as Kubeflow, Argo, Airflow, or similar frameworks.
• Experience building offline ML experimentation platforms, model registries, experiment tracking systems, or training orchestration frameworks.
• Experience building and operating agentic AI systems, including multi-agent orchestration, autonomous workflows, and agent communication/runtime frameworks (e.g., MCP, A2A, and orchestration systems) is a strong plus
• Experience running end-to-end model development and iteration cycles at scale is a plus

Expert Career Tips for Senior Machine Learning Systems Engineer, Ads ML Experience Platform Roles

To succeed in a competitive market as a Senior Machine Learning Systems Engineer, Ads ML Experience Platform, you need more than just technical skills. Here are some expert strategies to elevate your profile:

• Build a Strong Portfolio: For technical roles, a clean GitHub or a personal project site is essential. For non-technical roles, a case study portfolio demonstrating problem-solving and impact is equally valuable. Show, don't just tell, what you have achieved in your previous positions.
• Master the Narrative: When interviewing, use the STAR method (Situation, Task, Action, Result) to structure your answers. Quantify your results wherever possible—mentioning "increased efficiency by 20%" is much more impactful than saying "improved efficiency."
• Continuous Learning: The industry moves fast. Whether it's staying updated with the latest AI tools or mastering a new management methodology, continuous professional development is key. Consider obtaining industry-recognized certifications that align with Senior Machine Learning Systems Engineer, Ads ML Experience Platform requirements.
• Networking: Connect with other professionals in similar roles. Join online communities, attend webinars, and engage in meaningful discussions on professional social networks. Often, the best opportunities come through referrals and community engagement.
• Soft Skills Matter: Communication, empathy, and leadership are often the deciding factors between two equally qualified technical candidates. Cultivate these skills as they are universally valued across all industries and seniority levels.

Additionally, research the specific company's culture and values. Tailoring your application to show how you align with their mission can significantly increase your chances of moving forward in the process.

Salary & Compensation

Salary not disclosed; typically competitive for the role.

Work Arrangement

Type: On-Site

Standard business hours at the office.

Comprehensive Application Strategy & Hiring Process

Applying for a new role is a marathon, not a sprint. Follow this strategic approach to maximize your success rate:

1. Initial Research & Tailoring

Don't send the same resume to every employer. Spend at least 30 minutes researching the company. Look for recent news, their product roadmap, and their team structure. Modify your summary and core competencies to reflect the specific keywords found in the job description.

2. The Perfect Cover Letter

If the application allows for a cover letter, use it to tell a story that your resume cannot. Explain why you are passionate about this specific company and how your unique background makes you the perfect fit for the challenges they are currently facing.

3. Navigating the Multi-Stage Interview

Most modern hiring processes involve 3-5 stages. This typically includes a recruiter screen, a technical or skill-based assessment, a peer interview, and a final leadership round. Prepare for each stage differently: focus on enthusiasm and fit for the recruiter, technical depth for the assessment, and strategic vision for the leadership round.

4. Post-Interview Follow-Up

Always send a personalized thank-you note within 24 hours of each interview. Reference a specific topic discussed during the call to demonstrate your active listening and genuine interest in the role.

By following these steps, you demonstrate a high level of professionalism and attention to detail that sets you apart from the average applicant.

Typical Interview Process

1. Resume screening
2. HR call
3. Skill interview
4. Final manager interview
5. Offer

Tip: Research the company's products and culture.

Global Market Intelligence & Relocation Insights

At JobSetuu, we specialize in helping talent navigate the global job market. Here is what you need to know about the current landscape in Global and beyond:

The demand for skilled professionals is increasingly borderless. For roles based in Global, understanding the local cost of living, visa requirements (if applicable), and cultural nuances is vital. If this is a remote role, consider the time zone alignment and the asynchronous communication culture of the hiring organization.

Relocation Support: Many forward-thinking companies offer relocation packages that include moving stipends, temporary housing, and legal assistance with work permits. When evaluating an offer, look beyond the base salary—consider the total compensation package, including equity, bonuses, and healthcare benefits.

Work-Life Balance Trends: Hybrid and remote work have become standard in many regions. Research the local labor laws and common practices regarding work hours and vacation time to ensure the role aligns with your lifestyle goals.

Leveraging JobSetuu's tools can help you compare salaries across different cities and understand the "purchasing power" of your potential offer, ensuring you make an informed decision for your long-term career path.

Skills & Competency Roadmap for Professional Development

To remain competitive in Professional Development, we recommend focusing on the following core competencies over the next 12-18 months:

• Technical Mastery: Deepen your expertise in the core tools and languages relevant to your field. For developers, this might be cloud architecture; for marketers, it might be data-driven attribution modeling.
• AI Augmentation: Learn how to leverage generative AI and automation tools to increase your productivity. Understanding how to integrate these technologies into your workflow is becoming a non-negotiable skill.
• Leadership & Strategy: Even in individual contributor roles, the ability to think strategically and lead projects from inception to completion is highly valued. Focus on stakeholder management and high-level project planning.
• Data Literacy: The ability to interpret data and use it to drive decisions is essential across all business functions. Familiarize yourself with data visualization and basic analytical concepts.

By investing in these areas, you not only prepare yourself for the role you are applying for today but also build a resilient foundation for the opportunities of tomorrow.

Apply via JobSetuu

Discover your next career milestone on JobSetuu. This Senior Machine Learning Systems Engineer, Ads ML Experience Platform position is part of our commitment to bringing you the most relevant and high-impact job openings globally. At JobSetuu, we simplify your job search by aggregating premier listings and providing the tools you need to stand out. Don't miss the chance to elevate your professional journey—explore more opportunities and career insights on our platform today.