Remote Machine Learning Software Engineer

About the Role

Are you passionate about building intelligent systems that solve real-world problems at scale? This remote Machine Learning Software Engineer role offers an exciting chance to contribute to pioneering AI innovations that transform data into actionable insights. As a core contributor, you’ll have the opportunity to collaborate with cross-functional teams to deploy robust learning models, optimize algorithms, and create platforms that elevate user experience. With a salary of $165,729 annually, this is more than a job—it’s a chance to shape the future of AI, data science, and cloud-based applications from wherever you call home.

Key Responsibilities

Machine Learning Engineering

• Design, build, and deploy machine learning models that can scale with millions of data points.
• Continuously evaluate and refine predictive systems to improve accuracy, performance, and reliability.
• Develop intelligent software that leverages both supervised and unsupervised learning techniques.

Software Development

• Write production-ready code for model training pipelines, inference services, and monitoring tools.
• Partner with technical teams and product leads to integrate ML capabilities into cloud platforms and web applications.
• Ensure scalability and maintainability using modular software design

Data Infrastructure and Optimization

• Work with data engineers to build robust, low-latency pipelines that feed real-time learning systems.
• Apply deep understanding of data processing and distributed computing (e.g., Spark, Hadoop)
• Optimize training workflows and feature selection strategies for model accuracy and speed.

Experimentation and Research

• Drive research-based initiatives to evaluate new ML approaches and neural network architectures.
• Lead A/B testing experiments to validate enhancements and measure impact on product KPIs
• Contribute to internal documentation and publications to share insights across the team.

Tools and Technologies

Your daily toolkit will include state-of-the-art technologies and frameworks, carefully selected for performance and scalability:

• Programming Languages: Python, Scala, Java
• ML Frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost
• Data Platforms: AWS SageMaker, GCP AI Platform, Azure ML, Databricks
• Pipelines & Orchestration: Airflow, MLflow, Kubeflow
• Version Control & CI/CD: Git, Jenkins, Docker, Kubernetes

You’ll also benefit from advanced MLOps tooling that automates deployment, scaling, and observability across the lifecycle.

Ideal Work Environment

This role offers complete remote flexibility, allowing you to contribute from your ideal workspace—whether it's a home office, coworking hub, or anywhere in between. You’ll operate within a team culture grounded in:

• Ownership and Impact: Everyone’s voice matters. Ideas are valued and acted upon quickly.
• Agile Collaboration: Work closely with peers in real-time and asynchronous formats using tools like Slack, Notion, and Zoom.
• Continuous Learning: Access to training resources, certification sponsorships, and dedicated time for innovation sprints.
• Inclusive Culture: A remote-first workplace that values equity, neurodiversity, and respect across global time zones.

Skills and Qualifications

We are looking for someone whose background, curiosity, and ambition align with the complexity and scope of our AI systems.

Core Qualifications

• Proven experience (3+ years) in machine learning engineering, applied AI, or intelligent systems.
• Strong coding proficiency with an emphasis on Python and ML tooling
• In-depth understanding of algorithms, model evaluation, and optimization strategies
• Familiarity with cloud platforms (AWS, GCP, or Azure)
• Practical experience in real-world model deployment and lifecycle management

Preferred Qualifications

• Master's or PhD in Computer Science, Data Science, or a related quantitative discipline
• Exposure to reinforcement learning, deep learning, or generative AI concepts
• Prior work on scalable recommendation systems, predictive analytics, or NLP applications
• Experience in a remote or globally distributed engineering team

Career Growth & Development

In this position, your contribution doesn’t just support the business—it shapes it. From spearheading initiatives in automation to mentoring junior team members, you’ll have the autonomy to define your professional path.

• Grow Into Leadership: Advance into technical leadership roles or cross-functional team ownership.
• Influence Strategy: Help define architecture and machine learning strategy that scales globally
• Lead Innovation: Launch new AI products and enhance systems with explainability and ethical design

Why This Role Matters

In an age where data-driven decisions define market leaders, your work as a Machine Learning Software Engineer becomes pivotal. From crafting real-time inference engines to streamlining user personalization through intelligent automation, your solutions will shape user experiences across industries. Your role ensures that artificial intelligence is not just robust but ethical, scalable, and deeply human-centric.

What Success Looks Like

• Launching ML solutions that drive measurable business outcomes
• Delivering highly available and low-latency inference systems
• Driving innovation while ensuring transparency, fairness, and accountability in AI models
• Consistently mentoring and supporting peer growth in a remote, collaborative space

Ready to Shape the Future?

We’re looking for engineers who not only solve problems but envision what’s next. If you’re passionate about working with advanced machine learning systems, thrive in a fully remote environment, and want your work to matter on a global scale, we’d love to meet you.

Submit your application and lend your expertise to a mission that values innovation, impact, and inclusivity. Your next challenge starts here.