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Sr. IT Engineer - ML

July 1, 2026

Responsibilities:

The Machine Learning domain encompasses the application of algorithms and models to enable computers to learn from and make predictions or decisions based on data. This domain is generally a subset of the AI or Data Domain.
Collaborate with leaders, business analysts, project managers, IT architects, technical leads, and other engineers, along with internal customers, to understand requirements and develop needs according to business requirements for AI solutions.
Maintain and enhance existing enterprise services, applications, and platforms using domain-driven design and test-driven development.
Troubleshoot and debug complex issues; identify and implement solutions.
Create detailed project specifications, requirements, and estimates.
Research and implement new AI technologies to enhance current processes, security, and performance.
Work closely with data scientists and product teams to build and deploy machine learning models, focusing on the technical aspects of model deployment.
Implement and optimize Python-based ML pipelines for data preprocessing, model training, and deployment.
Monitor model performance and implement strategies for bias mitigation and explainability. Responsible for ensuring models are scalable and efficient in production environments.
Write and maintain code for model training and deployment, collaborating with software engineers to integrate models into applications.
Partner with a diverse team of experts, leveraging cutting-edge technologies to build scalable and impactful AI solutions.

Requirements:

Skills Required: Python, Databricks, Azure Databricks, ADF, Azure ML, Azure, AWS, GCP, Machine Learning, ML, NLP, Gen AI, Tensorflow, Pytorch, and TensorFlow.
Experience Range: 5 - 9 years.
Bachelor's degree in Computer Science, Computer Engineering, Data Science, Information Systems (CIS / MIS), Engineering, or a related technical discipline, or equivalent experience / training.
3+ years of full Software Development Life Cycle (SDLC) experience designing, developing, and implementing large-scale machine learning applications in hosted production environments.
3+ years of professional, design, and open-source experience.

Preferred Qualifications - Education and Prior Job Experience:

Master's degree in Computer Science, Computer Engineering, Data Science, Information Systems (CIS / MIS), Engineering, or a related technical discipline, or equivalent experience / training.
5 years of full Software Development Life Cycle (SDLC) experience designing, developing, and implementing large-scale machine learning applications
Airline Industry experience.

Programming and Backend Development:

Python (backend services/APIs, automation, testing).
SQL (advanced querying, window functions, optimization, data modeling fundamentals).
REST APIs, JSON, service integration patterns.

AI Agents / Agent Frameworks (Must-have):

Hands-on experience with at least one enterprise-grade agent framework, such as LangGraph/Crew AI/Autogen (or equivalent agent orchestration frameworks), Copilot Studio agents/OpenAI agents (or equivalent).
Agent orchestration, tool/function calling, structured outputs, evaluation, and iteration patterns.

Analytics, Reporting, and Dashboards:

Power BI and/or Tableau.
Metrics definition, reporting automation, executive-ready dashboards.

Cloud Platforms:

Microsoft Azure or AWS.
Experience deploying data/AI workloads in cloud environments.

Data and Integration:

Data pipelines/ELT concepts, dataset curation for analytics.
Integration with an enterprise risk assessment and governance workflow platform (tool-agnostic).

AI/ML Fundamentals:

Applied understanding of ML lifecycle concepts.
Familiarity with LLM concepts like prompting, context handling, grounding patterns like RAG, Evals, Agent Behavior Monitoring etc.

Governance, Risk, and Regulatory Knowledge:

Working on awareness of AI/data regulations and governance expectations such as GDPR, the EU AI Act, and similar privacy/AI governance frameworks.
Understanding of governance controls: evidence capture, auditability, traceability, Observability, exception management, and reporting.

Software Engineering Practices:

Object-oriented design and clean coding principles.
Version control (Git) and CI/CD fundamentals.
Testing practices (unit/integration), documentation, logging/monitoring, operational readiness.

Licenses and Certifications (Preferred, not required):

Microsoft Certified: Azure Data Engineer Associate / Azure Developer Associate / Azure AI Engineer Associate.
AWS Certified Developer - Associate / AWS Certified Data Engineer - Associate (or equivalent AWS certifications).
Power BI or Tableau certification (if applicable/available).
Any relevant certifications in data privacy or AI governance/risk (e. g., privacy fundamentals, responsible AI).

Methodologies and Tools (Preferred):

Experience working in Agile (Scrum/Kanban) environments.
Familiarity with DevOps toolchains (e. g., CI pipelines, code quality checks, artifact repos).

Language/Communication Skills:

Ability to effectively communicate both verbally and in writing with all levels within the organization.
Physical ability necessary to safely and successfully perform the essential functions of the position, with or without any legally required reasonable accommodations that do not pose an undue hardship.

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Common Interview Questions And Answers

1. HOW DO YOU PLAN YOUR DAY?

This is what this question poses: When do you focus and start working seriously? What are the hours you work optimally? Are you a night owl? A morning bird? Remote teams can be made up of people working on different shifts and around the world, so you won't necessarily be stuck in the 9-5 schedule if it's not for you...

2. HOW DO YOU USE THE DIFFERENT COMMUNICATION TOOLS IN DIFFERENT SITUATIONS?

When you're working on a remote team, there's no way to chat in the hallway between meetings or catch up on the latest project during an office carpool. Therefore, virtual communication will be absolutely essential to get your work done...

3. WHAT IS "WORKING REMOTE" REALLY FOR YOU?

Many people want to work remotely because of the flexibility it allows. You can work anywhere and at any time of the day...

4. WHAT DO YOU NEED IN YOUR PHYSICAL WORKSPACE TO SUCCEED IN YOUR WORK?

With this question, companies are looking to see what equipment they may need to provide you with and to verify how aware you are of what remote working could mean for you physically and logistically...

5. HOW DO YOU PROCESS INFORMATION?

Several years ago, I was working in a team to plan a big event. My supervisor made us all work as a team before the big day. One of our activities has been to find out how each of us processes information...

6. HOW DO YOU MANAGE THE CALENDAR AND THE PROGRAM? WHICH APPLICATIONS / SYSTEM DO YOU USE?

Or you may receive even more specific questions, such as: What's on your calendar? Do you plan blocks of time to do certain types of work? Do you have an open calendar that everyone can see?...

7. HOW DO YOU ORGANIZE FILES, LINKS, AND TABS ON YOUR COMPUTER?

Just like your schedule, how you track files and other information is very important. After all, everything is digital!...

8. HOW TO PRIORITIZE WORK?

The day I watched Marie Forleo's film separating the important from the urgent, my life changed. Not all remote jobs start fast, but most of them are...

9. HOW DO YOU PREPARE FOR A MEETING AND PREPARE A MEETING? WHAT DO YOU SEE HAPPENING DURING THE MEETING?

Just as communication is essential when working remotely, so is organization. Because you won't have those opportunities in the elevator or a casual conversation in the lunchroom, you should take advantage of the little time you have in a video or phone conference...

10. HOW DO YOU USE TECHNOLOGY ON A DAILY BASIS, IN YOUR WORK AND FOR YOUR PLEASURE?

This is a great question because it shows your comfort level with technology, which is very important for a remote worker because you will be working with technology over time...