MLOps Field Engineer

Jobgether SRL; Canada; Remote; CAD 110,000 - 140,000; Full time

Benefits offered by this job

Fully distributed work environment

Learning & development budget (USD 2,0

Job summary

Jobgether SRL is seeking a MLOps Field Engineer based in Canada to design and deliver modern AI/ML architectures using open source tech, Linux, Kubernetes, and cloud platforms. You will work directly with customers, architects, and sales to implement distributed ML and data processing solutions in hybrid environments.

The role emphasizes hands-on implementation, solution architecture, and technical consulting with travel up to 30%.

Qualifications

• MLOps, data engineering, or cloud infra experience with large-scale workloads.
• Linux, virtualization, containers, networking, and cloud platforms knowledge.
• Kubernetes experience; familiarity with AWS/Azure/GCP helps.
• Proficiency in Python; other languages like R or Rust a plus.
• Strong English communication and customer-facing presentation skills.

Responsibilities

• Design and architect AI/ML, MLOps, data engineering and cloud solutions for customer workloads.
• Engage customers to translate requirements into practical infra and open-source designs.
• Deploy, test, troubleshoot and hand over solutions to support teams.
• Develop automation and Kubernetes capabilities using Python and related tech.
• Deliver workshops, demos, and training on cloud, Linux, AI/ML and OSS.
• Travel internationally up to 30% for engagements and events.

Skills

MLOps

Data engineering

Cloud infrastructure

Linux

Kubernetes

Python

Open source

English

Education

Bachelor's degree in Computer Science or related

Tools

Kubeflow

OpenStack

Spark

AWS/Azure/GCP

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a MLOps Field Engineer based in Canada.

This role is ideal for an MLOps or cloud engineering professional who enjoys solving complex technical challenges directly with customers. You will design and deliver modern AI/ML architectures using open source technologies, Linux, Kubernetes, and public or private cloud infrastructure. The position combines technical consulting, solution architecture, hands‑on implementation, and customer engagement rather than traditional software development. You will work on large-scale challenges involving distributed machine learning, real‑time data processing, hybrid cloud environments, and advanced analytics. As part of a global Field Engineering team, you will collaborate closely with sales, product, engineering, and enterprise customers. The role also provides exposure to emerging technologies and opportunities to influence technical roadmaps through real‑world customer insights.

Accountabilities

• Design and architect AI/ML, MLOps, data engineering, and cloud infrastructure solutions aligned with customer workloads and business requirements.
• Work across the Linux technology stack, including networking, storage, containers, applications, and infrastructure.
• Architect and deploy solutions using Kubernetes, Kubeflow, OpenStack, Spark, and related open source technologies.
• Deliver solutions across on-premises environments and major public cloud platforms, including AWS, Azure, and Google Cloud.
• Engage directly with customers to understand technical and business requirements and recommend appropriate open source solutions.
• Deploy, test, troubleshoot, and validate technical solutions before handing them over to support or managed services teams.
• Develop infrastructure automation and Kubernetes capabilities using Python and other relevant technologies.
• Deliver technical presentations, demonstrations, workshops, and training sessions covering cloud, Linux, AI/ML, and open source technologies.
• Collaborate closely with enterprise sales teams to support customer engagements, develop opportunities, and achieve shared commercial objectives.
• Work with product and engineering teams to communicate customer requirements, provide technical feedback, and influence product and technology roadmaps.
• Contribute to a collaborative engineering culture and share knowledge across a globally distributed technical community.
• Travel internationally for customer engagements, industry events, internal events, and project-related activities, with travel potentially reaching 30% of working time.

Requirements

• Professional experience in MLOps, data engineering, big data, cloud infrastructure, or the deployment of machine learning and analytics solutions.
• Practical experience with Linux, virtualization, containers, networking, and cloud infrastructure.
• Experience with Kubernetes and familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Working knowledge of MLOps, AI/ML infrastructure, data processing pipelines, distributed systems, or large-scale analytics environments.
• Intermediate Python programming skills, with experience in another language such as R or Rust considered an advantage.
• Understanding of open source technologies and an interest in enterprise applications of private cloud, machine learning, AI, data, and analytics.
• Ability to design technical architectures and translate complex customer requirements into practical infrastructure and solution designs.
• Strong customer-facing communication skills, with the ability to explain technical concepts through presentations, demonstrations, workshops, and discussions.
• Business‑minded approach with the ability to balance technical quality, customer needs, and commercial objectives.
• Demonstrated problem‑solving ability, initiative, and willingness to take ownership of complex projects.
• Strong interpersonal skills, curiosity, flexibility, accountability, and a results‑oriented mindset.
• Confidence to exchange feedback, challenge ideas respectfully, and contribute actively to technical discussions.
• Passion for technology demonstrated through personal projects, continuous learning, open source involvement, or technical initiatives.
• Strong written and spoken English with excellent presentation skills.
• A technical undergraduate degree or a compelling alternative educational or professional background.
• Ability to work effectively with colleagues and customers across multicultural, multinational, and distributed environments.
• Willingness and ability to travel internationally for customer meetings, industry events, and company gatherings.

Benefits

• Geographically adjusted compensation based on location, experience, and performance.
• Performance‑driven annual bonus or commission in addition to base compensation.
• Fully distributed work environment with twice‑yearly in‑person team sprints.
• Personal learning and development budget of USD 2,000 per year.
• Annual compensation review.
• Recognition rewards.
• 40 days of annual leave per year, including public holidays and company‑wide holiday periods.
• Maternity and paternity leave.
• Team Member Assistance Program and Wellness Platform.
• Opportunities to travel internationally and collaborate with colleagues in different locations.
• Priority Pass access and travel upgrades for eligible long‑haul company events.
• Hands‑on exposure to AI/ML infrastructure, data processing pipelines, distributed training, Kubernetes, and emerging open‑source technologies.
• Opportunities to work directly with customers across a wide range of industries and technical environments.