OPSWAT

Protects critical infrastructure from malware

Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeTimișoara, RomaniaNo salary listedIn-person

About the Job

Requirements

At least 3 years of hands-on experience as a Machine Learning Engineer, Data Scientist, or Applied Scientist, including delivering models to production.
A bachelor's or master's degree in Computer Science, Mathematics, Statistics, or a related field.
Strong Python skills and experience with NumPy, pandas, scikit-learn, and PyTorch or TensorFlow.
A solid grounding in statistics and machine learning fundamentals, including bias/variance, class imbalance, data leakage, and calibration.
Practical experience with AWS for data storage and training workloads.
Clear written and spoken English.

Responsibilities

Turn detection problems into well-posed machine learning problems with a clear hypothesis, baseline, and success criteria.
Build, label, and version datasets for training and evaluation.
Design, train, and tune models; analyze model errors and feed findings back into data, features, or architecture.
Define evaluation protocols, including metrics, data splits, held-out test sets, and thresholds tied to product constraints such as false-positive rate and latency.
Take models from experiment to production on AWS with MLOps and software engineers, including packaging and inference optimization.
Monitor deployed models for drift and drive retraining when needed.
Keep experiments reproducible and documented, and present results and trade-offs to engineering and product.

Desired Qualifications

Experience with experiment tracking and model registries such as MLflow, Weights & Biases, or similar tools.
Experience optimizing and packaging models for inference, including quantization, distillation, ONNX, and Docker.
Knowledge of file formats and binary analysis.
Background in cybersecurity, threat detection, or another adversarial domain.
Publications, open-source contributions, or a competitive machine learning track record.

OPSWAT, a global leader in IT, OT, and ICS critical infrastructure cybersecurity, delivers an end-to-end platform that gives public and private sector organizations and enterprises the critical advantage needed to protect their complex networks, secure their devices, and ensure compliance. Over the last 20 years our commitment to innovative technology has earned the trust of more than 1,700 organizations, governments, and institutions globally, solidifying our role in protecting the world’s critical infrastructure and securing our way of life.

What You Will Be Doing

Turn detection problems into well-posed ML problems with a clear hypothesis, baseline, and success criteria

Build, label, and version the datasets used for training and evaluation

Design, train, and tune models; analyze their errors and feed the findings back into data, features, or architecture

Define evaluation protocols: metrics, splits, held-out test sets, and thresholds tied to product constraints such as false-positive rate and latency

Take models from experiment to production on AWS together with MLOps and software engineers, including packaging and inference optimization

Monitor deployed models for drift and drive retraining when needed

Keep experiments reproducible and documented, and present results and trade-offs to engineering and product

What We Need From You

3+ years of hands-on experience as a Machine Learning Engineer, Data Scientist, or Applied Scientist, with models delivered to production

Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field

Strong Python and the scientific stack (NumPy, pandas, scikit-learn, PyTorch or TensorFlow)

Solid grounding in statistics and ML fundamentals: bias/variance, class imbalance, leakage, calibration

Practical experience with AWS for data storage and training workloads

Clear written and spoken English

Nice to Have

Experience with experiment tracking and model registries (MLflow, Weights & Biases, or similar)

Experience optimizing and packaging models for inference (quantization, distillation, ONNX, Docker)

Knowledge of file formats and binary analysis

Background in cybersecurity, threat detection, or another adversarial domain

Publications, open-source contributions, or a competitive ML track record

OPSWAT is an equal opportunity employer. We celebrate diversity and are committed to providing an environment where equal employment opportunities are extended to all employees and applicants, free of discrimination and harassment of any type. All employment decisions are based on individual qualifications, job requirements, and business needs without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other category protected by federal, state, or local laws.

Recruiting Agencies: we do not accept unsolicited resumes from third party agencies for any of our open positions. To submit resumes for our jobs, there must be a recruiting contract approved by our legal team and endorsed by both parties. We are currently not accepting additional 3rd party agencies at this time.

About the Company

OPSWAT

Protects critical infrastructure from malware

OPSWAT provides cybersecurity solutions that protect critical infrastructure from malware and zero-day attacks by focusing on threat prevention and secure data transfer. Its products secure files and devices at all stages—entry, exit, and rest—ensuring secure access and safe data exchange. The company differentiates itself through deep specialization in high-risk sectors like energy, finance, and government, and by achieving widespread trust (notably 98% of U.S. nuclear power facilities) for its compliance-driven approach. Its goal is to help organizations maintain secure, compliant operations and minimize the risk of cyber compromise while keeping systems productive.

Company size: 1,001-5,000
Company stage: Growth Equity (Venture Capital)
Total funding: $125M
Headquarters: Tampa, FL
Founded: 2002

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