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Remote Machine Learning Engineer Jobs in Alaska (NOW HIRING)

Sedgwick

Data Engineer AI

Minto, AK · On-site +1

$118K - $142K/yr

Build and maintain Feature Stores and specialized datasets optimized for machine learning, ensuring ... LI-TS1 #remote Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace. If you're ...

York Risk Services

Data Engineer AI

Minto, AK · On-site +1

$118K - $142K/yr

Build and maintain Feature Stores and specialized datasets optimized for machine learning, ensuring ... LI-TS1 #remote Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace. If you're ...

Sedgwick

Senior Engineer - LLMOps & MLOps

Minto, AK · On-site +1

$108K - $148K/yr

We are looking for a "day-one" engineer to own the production lifecycle of our AI initiatives. Your ... remote #LI-TS1 Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace. If you're ...

York Risk Services

Senior Engineer - LLMOps & MLOps

Minto, AK · On-site +1

$108K - $148K/yr

We are looking for a "day-one" engineer to own the production lifecycle of our AI initiatives. Your ... remote #LI-TS1 Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace. If you're ...

ABB

Service Sales Specialist

Anchorage, AK · Remote

... learning, and creative problem-solvingthat allows the right candidate to handle multiple work ... Remote {#LI-Remote}, this role provides support for the East Coast and will require East Coast ...

Huna Totem Corporation

IT Specialist (Juneau)

Juneau, AK · On-site +1

$75K - $85K/yr

Juneau or Hoonah, Alaska preferred; remote work may be considered based on experience Reports To ... Position Summary Huna Totem Corporation is seeking an IT Specialist with a developer emphasis to ...

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All JobsMachine Learning Engineer JobsRemote Machine Learning Engineer JobsRemote Machine Learning Engineer Jobs in Alaska

Remote Machine Learning Engineer information

See Alaska salary details

$33.9K

$138.7K

$208.4K

How much do remote machine learning engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for remote machine learning engineer in Alaska is $138,677.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,300.00 and $166,900.00 per year, depending on experience, location, and employer.

What engineers make $300,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually. High compensation often reflects expertise, leadership roles, or working in competitive industries such as tech or finance, especially in organizations valuing AI development.

What are some typical challenges faced by Remote Machine Learning Engineers, and how are they addressed?

Remote Machine Learning Engineers often face challenges such as coordinating across different time zones, ensuring smooth communication with team members, and accessing large datasets or secure environments remotely. Organizations commonly address these by using robust collaboration tools (like Slack, GitHub, and Jira), establishing clear documentation, and setting regular virtual meetings to maintain alignment. Many companies also provide secure remote environments or VPN access for handling sensitive data and code. Proactive communication and organized workflows help mitigate these challenges, enabling engineers to remain productive and connected to their teams.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role is unlikely to be fully replaced by AI itself. Instead, AI tools can augment their work by automating routine tasks, allowing MLEs to focus on complex problem-solving, model optimization, and system integration. Continuous learning and expertise in programming, data handling, and model evaluation remain essential for MLEs in an evolving AI landscape.

What are the key skills and qualifications needed to thrive in the Remote Machine Learning Engineer position, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in computer science, mathematics, and experience with machine learning algorithms, typically supported by a relevant degree and prior project work. Proficiency with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms is crucial, and certifications like AWS Certified Machine Learning can enhance your profile. Excellent communication, self-motivation, and time-management skills are also essential for collaborating across remote teams and meeting project goals. These combined technical and soft skills are vital for developing effective machine learning solutions while ensuring productivity and collaboration in a virtual work environment.

What is a Remote Machine Learning Engineer job?

A Remote Machine Learning Engineer designs, develops, and deploys machine learning models while working from a remote location. They preprocess data, train and optimize models, and integrate them into production systems. Their role often involves collaborating with data scientists, software engineers, and stakeholders to solve complex problems using AI. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and cloud computing knowledge are essential. Remote ML engineers must also communicate effectively and manage their time efficiently to work asynchronously with teams.

Can ML engineers work remotely?

Yes, many machine learning engineers work remotely, especially in roles that involve programming, data analysis, and model development using tools like Python, TensorFlow, or PyTorch. Remote work arrangements depend on the employer's policies and the specific project requirements, but it is common in the tech industry for ML engineers to work from home or other locations.
What are the most commonly searched types of Machine Learning Engineer jobs in Alaska? The most popular types of Machine Learning Engineer jobs in Alaska are:
What are popular job titles related to Remote Machine Learning Engineer jobs in Alaska? For Remote Machine Learning Engineer jobs in Alaska, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Engineer jobs in Alaska look for? The top searched job categories for Remote Machine Learning Engineer jobs in Alaska are:
Remote Machine Learning Engineer jobs near you
Data Engineer AI

Data Engineer AI

Sedgwick

Minto, AK • On-site, Remote

$118K - $142K/yr

Other

Posted 27 days ago

Sedgwick rating

7.6

Company rating: 7.6 out of 10

Based on 313 frontline employees who took The Breakroom Quiz

188th of 278 rated insurance

Job description

By joining Sedgwick, you'll be part of something truly meaningful. It's what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there's no limit to what you can achieve.

Newsweek Recognizes Sedgwick as America's Greatest Workplaces National Top Companies

Certified as a Great Place to Work

Fortune Best Workplaces in Financial Services & Insurance

Data Engineer AI

Role Overview

As a Senior Data Engineer within the Transformation Office, you are the hands-on architect of the data supply chain for our most advanced initiatives. You will be responsible for the "heavy lifting" required to fuel Data Science models and AI applications with high-fidelity data. Your mission is to build the pipelines that bridge our legacy on-prem systems (Mainframes, SQL Server, DB2) with our modern Snowflake environment and AWS/Azure AI stacks. You are a "day-one" builder who ensures that data is not just moved, but engineered for the specific requirements of model training, feature stores, and RAG-based AI systems.

Key Responsibilities

Hybrid Data Pipeline Execution: Design and implement robust ETL/ELT pipelines to ingest data from legacy on-prem sources, AWS (S3/RDS), and Azure (Blob/SQL), centralizing it for consumption in Snowflake and AI services.

Engineering for Data Science: Build and maintain Feature Stores and specialized datasets optimized for machine learning, ensuring Data Scientists have immediate access to clean, versioned, and statistically valid data.

Engineering for AI (RAG & LLMs): Develop the data pipelines required for Generative AI, including the automated extraction, chunking, and loading of unstructured data into vector stores across AWS and Azure.

Snowflake Power-User Execution: Act as the technical lead for our Snowflake data warehouse, implementing sophisticated data modeling, Snowpipe automation, and compute optimization to support high-concurrency AI workloads.

Legacy "Back-Reach" Engineering: Execute non-invasive data extraction patterns to unlock mission-critical data from decades-old on-premise systems without disrupting core business operations.

Multi-Cloud Orchestration: Manage complex, cross-platform data workflows using Airflow, Step Functions, or Azure Data Factory, ensuring the synchronization of data across our multi-cloud AI posture.

IT & Security Diplomacy: Partner directly with central IT, Database Administrators, and Security teams to solve connectivity hurdles (PrivateLink, IAM, firewalls) and secure "license to operate" for new data flows.

Data Quality for Model Integrity: Implement automated validation and observability layers to detect data drift and quality issues that could compromise the accuracy of production AI and Data Science models.

Cost & Performance Management: Drive the efficiency of our data stack by optimizing storage and query performance in Snowflake, AWS, and Azure to manage the ROI of the Transformation Office.

Direct Stakeholder Collaboration: Work as a dedicated engineering partner to MLOps and Data Science teams to rapidly iterate on data requirements for evolving AI use cases.

Qualifications

Education: Bachelor's degree in Computer Science, Data Engineering, or a related field is required. A Master's degree is highly desirable.

Proven Execution: 6+ years of hands-on data engineering experience, with a track record of building production-grade pipelines for Data Science and AI in multi-cloud environments.

Snowflake Mastery: Expert-level proficiency in Snowflake architecture, including data sharing, performance tuning, and the integration of Snowflake with external cloud AI services.

Multi-Cloud Proficiency: Advanced, hands-on knowledge of AWS (S3, Glue, Lambda) and Azure (Data Factory, Synapse) data services.

Technical Stack: Mastery of Python, SQL, and PySpark. Deep experience with data orchestration and containerization (Docker).

Legacy Expertise: Proven ability to interface with "old world" tech (on-premise SQL, Mainframe extracts, flat files) and transform it for modern cloud consumption.

AI/DS Fluency: A strong understanding of the specific data needs for Machine Learning (feature engineering) and Generative AI (vectorization and embedding pipelines).

Execution Mindset: A "get-it-done" attitude, capable of navigating enterprise bureaucracy and technical debt to ship code at the speed required by a Transformation Office.

#LI-TS1 #remote

Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace.

If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.

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