Sr. Machine Learning Engineer
Sr. Machine Learning Engineer

Sr. Machine Learning Engineer

Full-Time 43200 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead complex ML engineering projects and develop scalable ML architecture.
  • Company: Fortra is a dynamic company focused on cybersecurity and innovative tech solutions.
  • Benefits: Enjoy competitive salaries, flexible work options, and personal development opportunities.
  • Why this job: Join a fun, collaborative team tackling meaningful challenges in machine learning.
  • Qualifications: 7+ years in engineering/data science, with strong ML engineering expertise required.
  • Other info: Mentorship opportunities available; ideal for those passionate about cybersecurity.

The predicted salary is between 43200 - 72000 £ per year.

Whether you’re an experienced professional or just getting started, your contributions matter at Fortra. If you’re passionate about tackling meaningful challenges alongside talented team members committed to helping each other succeed, all while having lots of fun, we want to hear from you. We offer competitive benefits and salaries, personal and professional development opportunities, flexibility, and much more !

At Fortra, we’re breaking the attack chain. Ready to join us?

This position is responsible for developing, enhancing, and maintaining our Machine Learning pipelines and data science solutions including data pipelines, infrastructure, and deployment of machine learning models. The scope of the role includes both existing software products and new products in development. The ideal candidate has a strong commitment to excellence, brings a wealth of expertise in ML Engineering, is a creative problem solver, and a team player.

WHAT YOU\’LL DO

  • Lead highly complex ML engineering projects with extensive latitude for independent judgment.
  • Design, develop, document, test, and debug software engineering solutions for both customer-facing applications and internal use.
  • Deploy, scale, and maintain machine learning models in production environments.
  • Develop scalable ML architecture and pipelines.
  • Collaborate with data scientists to optimize, test, and evaluate ML models.
  • Identify and evaluate new platforms and technologies to enhance our existing systems.
  • Follow and help define and enforce our development best practices and standards.
  • Provide mentorship and assistance to less experienced team members.
  • Collaborate with architects and engineering managers to maintain development roadmaps and prioritize new features.
  • Engage with data science and engineering teams to understand requirements and constraints for multiple products.
  • Share your technical knowledge and MLOps framework expertise with team members.
  • Maintain up-to-date knowledge of related MLOps and data science topics and technologies.
  • Serve as the technical expert on the deployment and benchmarking of ML models including LLMs, and generative models.
  • Acquire domain expertise in at least one cybersecurity application area.
  • Write technical documentation based on architectural design and stated engineering requirements.

QUALIFICATIONS

  • At least 7 years of experience in engineering and/or data science roles is required with at least 1 year of senior role experience included. Multi-year experience as an ML engineer is desirable.
  • Strong academic background (M.S or PhD program in a technical field) is an adequate substitute for a few years of industry experience.
  • Thorough knowledge of software engineering and data science techniques and methodologies, and experience leading projects applying these methodologies.
  • Extensive experience developing system architecture and solving engineering problems in at least one major programming language such as Python, Java, or C++.
  • Comprehensive MLOps background and expertise in data processing, model training, and deployment of models as microservices.
  • Substantial experience integrating applications with cloud technologies such as AWS.
  • Proven track record of deploying and benchmarking ML models in production environments.
  • Expertise in MLOps frameworks such as MLflow and Kubeflow is nice to have.
  • Solid experience with Python-based frameworks such as PyTorch, TensorFlow, and scikit-learn is a plus.
  • Demonstrated ability to collaborate with engineering leads, software architects, and other stakeholders to advance engineering and data science projects.
  • Led multiple projects to completion in a small team.
  • Proven experience assisting or providing mentorship to junior engineers.
  • Excellent communication and presentation skills. Ability to convey complicated technical topics to non-technical people both verbally and in writing.
  • Demonstrated excellent problem solving ability and critical thinking skill with a variety of engineering challenges.
  • Comfortable and enthusiastic about sharing technical knowledge with team members.
  • Interest in cybersecurity applications.

Visit our website to learn more about why employees choose to work for Fortra. Remember to connect with us on LinkedIn .

As an EEO/Affirmative Action Employer, all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, veteran or disability status.

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Sr. Machine Learning Engineer employer: Fortra

At Fortra, we pride ourselves on fostering a collaborative and innovative work environment where every team member's contributions are valued. With a strong emphasis on personal and professional development, competitive benefits, and a culture that encourages creativity and fun, we empower our employees to tackle meaningful challenges in the cybersecurity space. Join us in a location that not only offers cutting-edge technology but also a supportive community dedicated to your growth and success.
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Contact Detail:

Fortra Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Sr. Machine Learning Engineer

✨Tip Number 1

Familiarise yourself with the latest trends in machine learning and MLOps. Being able to discuss recent advancements or tools like MLflow and Kubeflow during your interview can showcase your passion and expertise in the field.

✨Tip Number 2

Prepare to demonstrate your problem-solving skills through practical examples. Think of specific projects where you led ML engineering efforts, and be ready to explain your approach and the impact of your work.

✨Tip Number 3

Network with current employees or professionals in the field on platforms like LinkedIn. Engaging with them can provide insights into the company culture and expectations, which can be invaluable during your application process.

✨Tip Number 4

Showcase your collaborative spirit by preparing examples of how you've worked with cross-functional teams. Highlighting your ability to communicate complex technical concepts to non-technical stakeholders will set you apart.

We think you need these skills to ace Sr. Machine Learning Engineer

Machine Learning Engineering
Data Science Techniques
Software Development
Python Programming
Java or C++ Programming
MLOps Frameworks (e.g., MLflow, Kubeflow)
Cloud Technologies (e.g., AWS)
Model Deployment and Benchmarking
Data Processing and Model Training
Scalable ML Architecture Design
Technical Documentation Writing
Collaboration with Data Scientists
Project Management
Mentorship and Team Leadership
Problem-Solving Skills
Excellent Communication Skills
Cybersecurity Knowledge

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning engineering, data science, and software development. Emphasise your expertise in programming languages like Python, Java, or C++, and any MLOps frameworks you are familiar with.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for machine learning and cybersecurity. Mention specific projects you've led or contributed to, and how they align with the responsibilities outlined in the job description.

Showcase Your Problem-Solving Skills: In your application, provide examples of complex engineering challenges you've tackled. Highlight your critical thinking skills and how you've successfully collaborated with teams to deliver solutions.

Highlight Continuous Learning: Mention any recent courses, certifications, or workshops related to machine learning, data science, or cybersecurity. This shows your commitment to staying updated with industry trends and technologies.

How to prepare for a job interview at Fortra

✨Showcase Your Technical Expertise

Be prepared to discuss your experience with machine learning models, MLOps frameworks, and programming languages like Python or Java. Highlight specific projects where you've successfully deployed ML models in production environments.

✨Demonstrate Problem-Solving Skills

Expect to face technical challenges during the interview. Use examples from your past work to illustrate how you approached complex engineering problems and the solutions you implemented.

✨Emphasise Collaboration and Mentorship

Since the role involves working closely with data scientists and mentoring junior engineers, share experiences that showcase your ability to collaborate effectively and support team members in their development.

✨Stay Updated on Cybersecurity Trends

Given the focus on cybersecurity applications, demonstrate your knowledge of current trends and technologies in this field. Discuss any relevant experience or interest you have in applying ML to cybersecurity challenges.

Sr. Machine Learning Engineer
Fortra

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