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Remote Machine Learning Postdoc Jobs in Pflugerville, TX

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

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Remote Machine Learning Postdoc information

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Postdoc, and why are they important?

A Remote Machine Learning Postdoc requires a PhD in computer science, statistics, or a related field, with expertise in machine learning algorithms, statistical modeling, and research methodologies. Proficiency in programming languages like Python or R, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with version control systems (e.g., Git) are typically necessary. Strong written and verbal communication, self-motivation, and collaboration skills are vital for remote research and effective teamwork. These capabilities enable impactful independent research, smooth collaboration across distributed teams, and the successful dissemination of findings to the wider scientific community.

What is a Remote Machine Learning Postdoc?

A Remote Machine Learning Postdoc is a postdoctoral researcher specializing in machine learning who works predominantly or entirely from a location outside their host institution, often from home. Their work involves conducting advanced research, developing new algorithms, analyzing data, and publishing findings related to machine learning while collaborating virtually with faculty and research teams. This role is ideal for researchers seeking flexibility or those who cannot relocate but wish to contribute to academic or industrial research from a distance.

What are some common challenges faced by remote machine learning postdocs when collaborating with research teams?

Remote machine learning postdocs often encounter challenges related to communication and coordination, especially when working across different time zones or with teams that have varying schedules. Effective collaboration usually requires proactive communication through virtual meetings, shared code repositories, and regular progress updates. Building rapport with colleagues and staying engaged with ongoing research discussions can take extra effort remotely, but leveraging collaborative tools and participating in virtual seminars or group chats can help bridge the gap. Being organized and self-motivated is key to ensuring productive contributions to the team’s research objectives.
What job categories do people searching Remote Machine Learning Postdoc jobs in Pflugerville, TX look for? The top searched job categories for Remote Machine Learning Postdoc jobs in Pflugerville, TX are:
What cities near Pflugerville, TX are hiring for Remote Machine Learning Postdoc jobs? Cities near Pflugerville, TX with the most Remote Machine Learning Postdoc job openings:

Principal Site Reliability Engineer (SRE)

INFINITE CHOICE LLC

Austin, TX • Remote

$180K - $210K/yr

Full-time

Posted 3 days ago


Job description

About the Role

We're seeking an exceptional Principal Site Reliability Engineer to architect, design, and build our SRE foundation from the ground up at InfiniteChoice. This is a rare greenfield opportunity to establish SRE practices, develop custom tooling, and create the reliability culture that will support our platform serving millions of users and billions in transaction volume.

As our Principal SRE, you'll combine deep technical expertise with strategic vision to build world-class monitoring, observability, and automation systems. You'll have the autonomy to define our SRE processes, select technologies, and create the framework that ensures our systems are reliable, scalable, and performant.

Location: Remote - US based

What You Will DoSRE Foundation & Process Development
  • Build SRE practices from scratch - define SLIs, SLOs, error budgets, and reliability metrics

  • Establish incident response procedures, on-call rotations, and post-mortem processes

  • Create reliability engineering standards and best practices across all engineering teams

  • Develop disaster recovery and business continuity strategies

  • Design and implement capacity planning and performance optimization frameworks

Architecture & Tool Development
  • Drive architecture decisions for comprehensive application and infrastructure monitoring solutions

  • Design and develop custom SRE tools for automated monitoring, alerting, and remediation

  • Build observability platforms that provide deep insights into system performance and user experience

  • Create automation frameworks for deployment, scaling, and incident response

  • Architect logging, metrics, and tracing systems for distributed microservices environments

Google Cloud Infrastructure Excellence
  • Leverage Google Cloud Platform services to build resilient, scalable infrastructure

  • Implement cloud-native monitoring using Stackdriver, Cloud Monitoring, and Cloud Logging

  • Design auto-scaling and self-healing systems using GKE, Cloud Functions, and managed services

  • Optimize cloud costs while maintaining high availability and performance standards

  • Establish security and compliance frameworks within GCP environments

Innovation & Continuous Improvement
  • Research and implement cutting-edge SRE tools and methodologies

  • Leverage AI and machine learning for predictive analytics, anomaly detection, and automated remediation

  • Create dashboards and reporting systems that provide actionable insights to engineering and business teams

  • Establish feedback loops for continuous improvement of reliability and performance

  • Stay current with industry best practices and emerging technologies in the SRE space

What You Must HaveSRE & Infrastructure Expertise
  • 12+ years of experience in Site Reliability Engineering or Infrastructure Engineering

  • 5+ years in lead SRE roles building and scaling SRE teams and processes

  • Proven track record designing and implementing monitoring and observability solutions at scale

  • Deep understanding of distributed systems, microservices architectures, and cloud-native patterns

  • Experience with infrastructure as code, configuration management, and deployment automation

Google Cloud Platform Proficiency
  • Hands-on experience with Google Cloud Platform is required

  • Expertise with GCP monitoring and observability stack (Cloud Monitoring, Cloud Logging, Cloud Trace)

  • Experience with GKE, Compute Engine, Cloud Functions, and other core GCP services

  • Knowledge of GCP networking, security, and compliance capabilities

  • Understanding of GCP cost optimization and resource management

Technical Skills
  • Strong programming skills in Python, Go, Java, or similar languages

  • Experience with monitoring tools (Prometheus, Grafana, Datadog, New Relic, or similar)

  • Proficiency with containerization (Docker, Kubernetes) and orchestration platforms

  • Knowledge of CI/CD pipelines, automated testing, and deployment strategies

  • Understanding of database performance tuning and optimization (SQL and NoSQL)

AI & Automation
  • Familiarity with AI-driven development tools and methodologies is a huge plus

  • Experience with machine learning for operations (AIOps), anomaly detection, or predictive analytics

  • Knowledge of automated incident response and self-healing systems

  • Understanding of AI/ML tools for log analysis, pattern recognition, and intelligent alerting

Problem-Solving & Mindset
  • Strong analytical and troubleshooting skills for complex distributed systems

  • Experience with high-pressure incident response and crisis management

  • Detail-oriented with commitment to operational excellence and continuous improvement

  • Comfortable with ambiguity and building processes in a fast-growing environment

  • Passion for reliability, automation, and engineering best practices

  • Demonstrated experience building SRE programs and processes from the ground up is a HUGE plus

Education
  • Bachelor's degree in Computer Science, Engineering, or equivalent professional experience

  • Industry certifications (Google Cloud Professional, SRE or related certifications preferred)

What We Offer
  • Ground-floor opportunity to build SRE practices and culture from scratch

  • Full autonomy to define processes, select technologies, and establish best practices

  • Direct impact on platform reliability serving millions of users

  • Opportunity to create lasting engineering culture and operational excellence

  • Remote-first culture with in-person meeting in Dallas, TX on need basis

  • Collaborative environment with smart, passionate engineers and cross-functional teams

  • Access to cutting-edge technologies and AI-driven development tools

  • Competitive compensation, equity participation, and comprehensive benefits

Ready to Build World-Class Reliability?

Join us in creating the SRE foundation that will power InfiniteChoice's next phase of growth. If you're passionate about reliability engineering, love building systems from scratch, and want to establish the operational excellence that scales with our business, we'd love to hear from you.

About InfiniteChoice

InfiniteChoice was founded to help people find the experiences they want simply and effortlessly. We leverage a new type of business model and platform that uniquely applies automation and technology to solve the challenges of scale and complexity in experience discovery.


Existing business and marketing technologies can no longer handle the demands of connecting millions of consumers with vast inventories of experiences across a fragmented, global marketplace of people, partners, and providers.


Our mission is to disrupt this status quo by creating seamless connections between consumers and experiences. We're just at the beginning of this journey, but our approach is working: we've helped over 275 million visitors connect to millions of experiences, generating over $2 billion in revenue for our brands and partners.