Machine Learning / AI Engineer Senior - Databricks - Eng

OpenKrill; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Remote-friendly

Certifications covered (AWS, GCP, Dat"

English lessons

Birthday off

Job summary

Mutt Data is a remote startup hiring a Senior Machine Learning / AI Engineer to lead end-to-end AI/ML projects for clients, from problem translation to robust technical solutions.

The role emphasizes productionizing models, MLOps, and building scalable data infrastructures using Spark, Databricks, and Docker in a remote‑friendly environment.

Qualifications

• 4+ years in Generative/Agentic AI or ML systems in production.
• 3+ years in a customer-facing consulting or solutions architect role.
• Excellent verbal and written communication skills.
• Expertise in MLOps lifecycle management (versioning, testing, monitoring).
• Experience with containerization (Docker) and data pipelines.

Responsibilities

• Lead end-to-end AI/ML project implementations directly with clients.
• Communicate findings clearly to technical and non-technical stakeholders.
• Design and maintain production-grade AI/ML pipelines with CI/CD and MLOps practices.
• Architect end-to-end AI/ML systems based on customer requirements.
• Ensure production deployment readiness and scalable infrastructure.

Skills

Generative AI

Agentic AI

MLOps

Python

Docker

Spark

Tools

Databricks

CI/CD tools

Job description

Join Our Data Products and Machine Learning Development Remote Startup!

Mutt Data is a dynamic startup committed to crafting innovative systems using cutting‑edge Big Data and Machine Learning technologies.

We're looking for a Machine Learning / AI Engineer Senior to help take our expertise to the next level. If you consider yourself a data nerd like us, we'd love to connect!

What We Do

• - Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
• - Developing scalable data infrastructures, we enhance high‑level decision‑making, tailored to each client.
• - Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud‑based systems.
• - Using Generative AI, we help e‑commerce platforms and retailers create higher‑quality ads, faster.
• - Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
• - Developing recommendation models, we personalize user experiences in e‑commerce, streaming, and digital platforms, driving engagement and conversions.

Our Partnerships

• - Amazon Web Services
• - Astronomer
• - Databricks

Our Values

• - We are Data Nerds
• - We are Open Team Players
• - We Take Ownership
• - We Have a Positive Mindset

Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on!

Responsibilities

• - Serve as a primary technical consultant, leading and executing end‑to‑end AI/ML project implementationsdirectly with clients, translating complex business problems into robust technical solutions.
• - Exhibit excellent communication, presentation, and stakeholder management skills to clearlyarticulate technical findings, proposals, and project status to both technical and non‑technical audiences.
• - Design, build, and maintain production‑grade AI and ML pipelines, focusing on continuous integration,continuous delivery (CI/CD), and advanced MLOps/AIOps practices to ensure reliability and scalability ofmodels.
• - Implement and optimize cutting‑edge Generative and Agentic AI applications, demonstrating hands‑onexperience with technologies like multi‑agent orchestration, agent evaluation, and Retrieval AugmentedGeneration(RAG) Systems in a production setting.
• - Architect end‑to‑end AI/ML systems, designing both traditional Machine Learning- and Generative AI‑basedsolutions based on customer requirements
• - Manage underlying solution infrastructure necessary for production deployment, demonstrating proficiencyin technologies such as Docker, pipeline orchestrators, and lakehouse database systems like Databricks.
• - Leverage expertise in distributed computing frameworks, specifically in scalable machine learning and high‑performance data processing (e.g., using technologies like Apache Spark).
• - Contribute to the strategic growth of the AI FDE Practice, including participation in technical assignmentsand knowledge transfer activities.
• - Ensure all client engagements and training activities are properly documented and reported via designatedpartner platforms.

Required Skills

• - 4+ years of hands‑on professional experience developing, deploying, and managing Generative/Agentic AIor Machine Learning systems, with a mandatory requirement for productionizing and maintaining models ina live environment.
• - 3+ years of experience in a customer‑facing consulting or solutions architect role, focused on technicalimplementation and delivery.
• - Excellent verbal and written communication skills for effective client and internal team interaction.
• - Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automateddeployment best practices.
• - Demonstrable experience with infrastructure management, encompassing containerization (Docker) anddata pipeline orchestration.
• - Expertise in Python for data‑intensive and scalable AI/ML applications.
• - Demonstrated commitment to continuous learning in emerging AI/ML fields.

Perks

• - Remote‑first culture – work from anywhere!
• - AWS , DBT, Google Cloud, Azure & Databricks certifications fully covered
• - In‑Company English Lessons.
• - Birthday off + an extra vacation week (Mutt Week!)
• - Referral bonuses – help us grow the team & get rewarded!
• - Maslow: Monthly credits to spend in our benefits marketplace.
• - Annual Mutters' Trip – an unforgettable getaway with the team!
• - Monthly Childcare Reimbursement – Because supporting families matters too