Senior AI/ML Engineer – NLP and MLOps - Tieto Tech Consulting (m/f/d)

Tietoevry is hiring a Senior AI/ML Engineer – NLP and MLOps - Tieto Tech Consulting (m/f/d) in Sofia, Bulgaria. Level rates it ; you can apply on Tietoevry.

Level's read on this job

On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include MLOps, NLP and AI safety.
Level classifies it as a senior role.
Level lists 396 other open roles at Tietoevry.

AI in this role

ml-opsnlpai-safety

Tieto Tech Consulting (MentorMate from 2001 to 2026) provides design-led, data-centric, and AI-powered digital engineering & consulting services to enterprises worldwide. With a strong heritage of Nordic quality, local presence, and global-scale operations, we are backed by 8,500+ IT professionals. Our clients trust us for advanced data and analytics skills, top industry-specific expertise, specialized software R&D, and the capabilities of a multinational team. We are part of Tieto, a leading technology company with an annual revenue of approximately EUR 2bn.

Tieto Tech Consulting’s team in Bulgaria consists of 500+ professionals specializing in the development of tailored digital solutions in diverse industries.

We are seeking a Senior AI/ML Engineer with strong experience in natural language processing and production engineering. You will help develop and integrate services for information processing and extraction, using modern and classical NLP techniques. Working with product, data science and engineering teams, you will contribute to reliable cloud-based solutions and support their full lifecycle from development through deployment and operation.

Key responsibilities

Design, develop and maintain production-grade AI/ML services for information processing and extraction
Apply classical and modern NLP methods to address product and user needs
Build and integrate services using AWS cloud capabilities, including serverless and event-driven architectures
Contribute to DevOps practices and automation for reliable deployment and operation
Implement and improve MLOps workflows for model training, evaluation, deployment, monitoring and maintenance
Support model and data lifecycle management, including data preparation, versioning, quality and traceability
Explore and apply multi-agent systems where they provide value to product capabilities or engineering workflows
Collaborate with product, data science, architecture and engineering teams to turn requirements into maintainable solutions
Contribute to technical design discussions, code reviews, testing, documentation and continuous improvement

Required experience & qualifications

Professional experience engineering and operating production software systems
Hands-on experience with natural language processing, including classical and modern approaches
Experience with information processing, information extraction or related data-intensive solutions
Strong experience with AWS services and cloud-native engineering
Experience with DevOps practices, CI/CD and automation for production workloads
Experience with serverless and event-driven architectures
Experience with MLOps and deploying or operating machine learning models in production
Understanding of the model and data lifecycle, from preparation and validation through deployment, monitoring and maintenance
Excellent spoken and written English language skills

A significant advantage would be

Experience designing or working with multi-agent systems
Experience building AI/ML capabilities for digital health, life sciences or other regulated products
Familiarity with model observability, evaluation, governance or responsible AI practices
Experience with Python and common machine learning or NLP frameworks

At Tieto, we believe in the power of diversity, equity, and inclusion. We encourage applicants of all backgrounds, genders (m/f/d), and walks of life to join our team, as we believe that this fosters an inspiring workplace and fuels innovation. Our commitment to openness, trust, and diversity is at the heart of our mission to create digital futures that benefit businesses, societies, and humanity.
Diversity, equity and inclusion | Sustainability | Tieto

Stay alert to recruitment scams:
• Tieto only communicates via @tieto.com email addresses.
• We never ask candidates to pay fees or share financial details during recruitment.
• If you receive a suspicious message claiming to be from Tieto, don't respond — verify it via our official careers site.
• For more information visit Important Advisory Regarding Recruitment Fraud | Tieto Blog

How we rate this

Senior AI/ML Engineer – NLP and MLOps - Tieto Tech Consulting (m/f/d) at Tietoevry rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior AI/ML Engineer – NLP and MLOps - Tieto Tech Consulting (m/f/d) is an open job at Tietoevry.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Sofia, Bulgaria.
The job was posted on October 5, 2026.
Seniority: senior.
Applications are handled by Tietoevry. Apply on Tietoevry

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsNLPAI Safety

Also common in machine learning engineer jobs at this level

PyTorch LLM TensorFlow Deep learning Generative AI C++

Pay

Typical machine learning engineer job: $200k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
What NLP problem have you worked on, and how did you measure whether it actually worked?
How do you think about the risk of an AI system in this kind of role failing silently?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: ML Ops, NLP, and AI Safety. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

Want an expert to read your CV for this job?

Free. Send your CV and the role you want next. You get your review by email within 24 hours.

Get a free CV review Get your CV rewritten Check your resume with the ATS resume checker

Get new machine learning engineer jobs (Builds AI ●●●●) by email

One email a week with the new machine learning engineer jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.

Free. One email a week. Unsubscribe in one click.