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Remote Machine Learning Postdoc Jobs in Atlanta, GA

The Data Sherpas

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

... and machine learning models. What We Are Looking For: We are seeking an experienced and highly ... Flexible work environment and remote work options. Join us and be part of a team building ...

United Airlines

Teamcenter Agentic Engineer

Atlanta, GA · On-site +1

$46K - $111K/yr

Remote (Anywhere across USA) About the job you're considering As an Agentic Engineer, you will be ... Knowledge of machine learning frameworks such as TensorFlow, PyTorch, or similar technologies

DataAnnotation

QA Engineer - AI Trainer

Sandy Springs, GA · Remote

$50 - $100/hr

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 ...

DataAnnotation

SDLC Engineer - AI Trainer

Atlanta, GA · Remote

$50 - $100/hr

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 are popular job titles related to Remote Machine Learning Postdoc jobs in Atlanta, GA? For Remote Machine Learning Postdoc jobs in Atlanta, GA, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Postdoc jobs in Atlanta, GA look for? The top searched job categories for Remote Machine Learning Postdoc jobs in Atlanta, GA are:
Remote Machine Learning Postdoc jobs near you

Data Engineer - GCP

The Data Sherpas

Atlanta, GA • On-site, Remote

$110K - $132K/yr

Full-time

Medical, Dental, Vision

Posted 13 days ago

Job description

Who We Are:

We are a dynamic team focused on building innovative and scalable data solutions on Google Cloud Platform (GCP). Our Google Cloud Data Engineer will play a key role in designing, developing, and managing scalable data pipelines and data infrastructure, ensuring data availability, accuracy, and performance for business insights and machine learning models.


What We Are Looking For:

We are seeking an experienced and highly skilled Google Cloud Data Engineer who will be responsible for developing and managing data pipelines on GCP. The ideal candidate will bring strong expertise in cloud-based data processing, big data technologies, and data modeling to help us provide high-performance data solutions.


Responsibilities:

Data Pipeline Development and Management:

  • Design, build, and maintain scalable and reliable data pipelines using Cloud Dataflow, Cloud Pub/Sub, and Cloud Composer.
  • Develop ETL/ELT processes to process and transform large volumes of structured and unstructured data.
  • Optimize data pipeline performance, scalability, and reliability.
  • Ensure data processing and ingestion workflows are monitored and meet performance SLAs.

Data Storage and Management:

  • Design and implement data storage solutions using BigQuery, Cloud Storage, and Firestore.
  • Optimize data structures and partitioning for performance and cost efficiency.
  • Ensure data security, integrity, and availability in all storage solutions.
  • Manage data lifecycle policies and archiving processes.

Data Transformation and Processing:

  • Develop data transformation processes using BigQuery, Apache Beam, and Cloud Functions.
  • Implement data quality checks, validation rules, and monitoring solutions.
  • Support real-time and batch data processing needs.

Data Integration and Automation:

  • Integrate data from multiple sources, including APIs, databases, and third-party applications.
  • Automate data ingestion, transformation, and export using tools like Cloud Composer and Cloud Functions.
  • Ensure data consistency across different environments and systems.

Collaboration and Stakeholder Engagement:

  • Work closely with data scientists and analysts to understand data needs and business goals.
  • Provide technical guidance and best practices to the data engineering and business teams.
  • Collaborate with security and compliance teams to ensure data governance standards are met.

Performance Monitoring and Troubleshooting:

  • Monitor data pipeline performance and troubleshoot issues in real-time.
  • Analyze data pipeline failures and implement fixes to prevent recurrence.
  • Set up logging and monitoring using Stackdriver and Cloud Monitoring.


Qualifications:

  • Bachelor's degree in Computer Science, Data Engineering, or a related field; Master's degree is a plus.
  • 3+ years of experience in data engineering, with at least 2+ years working with Google Cloud Platform.
  • Google Professional Data Engineer certification is required.
  • Strong proficiency with GCP services such as BigQuery, Cloud Dataflow, Cloud Composer, Cloud Pub/Sub, Firestore, and Cloud Functions.
  • Hands-on experience with big data tools and frameworks such as Apache Beam, Hadoop, Spark, or Flink.
  • Hands-on experience with dbt.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Strong knowledge of SQL, data modeling, and query optimization.
  • Experience with CI/CD tools and version control (e.g., Git, Cloud Build).
  • Strong understanding of data governance, security, and compliance requirements.
  • Ability to manage large-scale data processing and real-time data pipelines.
  • Excellent problem-solving, analytical, and communication skills.
  • Must be a U.S. Citizen or Green Card holder.


Preferred Skills:

  • Experience with machine learning pipelines and AI/ML model deployment.
  • Familiarity with Terraform and Infrastructure as Code (IaC) principles.
  • Experience with NoSQL databases and key-value stores on GCP.
  • Knowledge of containerization and orchestration using Google Kubernetes Engine (GKE).


What We Offer:

  • Competitive salary and performance-based incentives.
  • Comprehensive health, dental, and vision coverage.
  • Professional development and training opportunities (including GCP certification).
  • Flexible work environment and remote work options.


Join us and be part of a team building innovative and scalable data solutions on Google Cloud Platform!


This position is open to multiple engagement models, including Permanent/Full-Time, Contract, or Corp-to-Corp (C2C) arrangements. We are looking for the best talent and are flexible on the employment structure for the right candidate.


This position is open to direct candidates only. We are not working with third-party agencies.


Candidates must be U.S. Citizens or Green Card holders.


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