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- Tasks: Develop and deploy machine learning models for various applications like intelligent search and recommendation systems.
- Company: Join an award-winning software company in Oxford, focused on AI-powered platforms across diverse industries.
- Benefits: Enjoy flexible working, a competitive salary, generous equity options, and a £1,000 annual learning budget.
- Why this job: Be part of a collaborative team making real-world impact with cutting-edge technology in a fast-paced environment.
- Qualifications: Strong Python skills, experience with ML frameworks, and familiarity with cloud platforms are essential.
- Other info: Hybrid work model with 2 days in the office and regular team events to foster community.
The predicted salary is between 40000 - 64000 £ per year.
Location: Oxford, UK (Hybrid – 2 days a week in office)
Salary: £50,000–£80,000 + bonus
About Us
We’ve partnered with an award-winning software company based in Oxford, building AI-powered platforms that help organisations extract insights, automate workflows, and drive smarter decisions across industries — from logistics and legal tech to research and government. Backed by leading UK tech investors and home to a team of engineers, product thinkers, and data scientists, we’ve scaled rapidly in the last 3 years and are now looking for a Machine Learning Engineer to help us push our platform to the next level. You’ll join a collaborative, pragmatic team that values clean code, creative problem-solving, and real-world impact. If you’re excited by applied ML and building things that get used — this is for you.
What You’ll Do Day to Day
- Develop, train, and deploy ML models in production for a range of use cases: document understanding, intelligent search, prediction engines, and recommendation systems
- Collaborate with product managers, software engineers, and customers to scope and define ML features
- Build scalable and reusable model pipelines and deploy using best-in-class MLOps practices
- Monitor, tune, and maintain models post-deployment with attention to performance, drift, and explainability
- Apply techniques like NLP (LLMs, transformers, embeddings), supervised/unsupervised learning, semi-structured data parsing, and anomaly detection
- Participate in sprint planning, code reviews, and architecture discussions — we’re a flat, fast-moving team
What You’ll Bring to the team
- Strong Python skills and experience with ML frameworks like scikit-learn, TensorFlow, PyTorch, Hugging Face
- Solid grasp of data wrangling, feature engineering, and model evaluation techniques
- Proficiency in designing and deploying production-ready ML pipelines
- Familiarity with cloud platforms (AWS/GCP/Azure) and tools like Docker, Airflow, MLflow, or Kubeflow
- Understanding of core ML algorithms and when to apply them: classification, clustering, regression, etc.
- Comfort with SQL and working in a software engineering environment (e.g., version control, CI/CD)
- Great communication skills — you can explain your ideas to technical and non-technical people alike
Nice to Have (but Not Deal-Breakers):
- Experience working with text-heavy datasets, OCR, or document intelligence
- Familiarity with vector search, semantic similarity, or RAG (Retrieval-Augmented Generation)
- Interest in Human-in-the-Loop ML, active learning, or explainable AI
- Prior startup or scale-up experience, ideally in B2B SaaS or platform-based ML
- Familiarity with TypeScript/JavaScript or APIs if you’ve worked closely with full-stack teams
What’s In It for You
- A meaningful role building real AI products that customers use daily
- Competitive salary and generous equity options
- Flexible working + hybrid model (beautiful central Oxford office)
- £1,000 annual learning & development budget
- 25 days annual leave + your birthday off
- Private medical insurance + mental health support
- Regular team events, tech meetups, and company retreats
Machine Learning Engineer employer: In Technology Group
Contact Detail:
In Technology Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the specific ML frameworks mentioned in the job description, such as TensorFlow and PyTorch. Consider building a small project or contributing to an open-source one using these tools to showcase your practical experience.
✨Tip Number 2
Engage with the community by attending local meetups or online webinars focused on machine learning and AI. Networking with professionals in the field can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss your experience with cloud platforms like AWS, GCP, or Azure during interviews. Having real-world examples of how you've deployed ML models in these environments will demonstrate your readiness for the role.
✨Tip Number 4
Brush up on your communication skills, especially in explaining complex ML concepts to non-technical stakeholders. Practising this can help you stand out, as the role requires collaboration with diverse teams.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly with Python and ML frameworks like TensorFlow or PyTorch. Emphasise any projects where you've developed, trained, or deployed ML models.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for applied machine learning and your understanding of the company's mission. Mention specific technologies and methodologies you are familiar with that align with the job description.
Showcase Your Projects: Include links to any relevant projects or GitHub repositories in your application. Highlight your contributions to ML pipelines, data wrangling, or any innovative solutions you've implemented.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail. Brush up on core ML algorithms, model evaluation techniques, and your experience with cloud platforms. Practice explaining complex concepts in simple terms, as communication is key.
How to prepare for a job interview at In Technology Group
✨Showcase Your Python Skills
As a Machine Learning Engineer, strong Python skills are essential. Be prepared to discuss your experience with Python and how you've used it in previous projects, especially with ML frameworks like scikit-learn, TensorFlow, or PyTorch.
✨Demonstrate Your Understanding of ML Concepts
Make sure you can explain core machine learning algorithms and when to apply them. Be ready to discuss your experience with data wrangling, feature engineering, and model evaluation techniques, as these are crucial for the role.
✨Prepare for Technical Questions
Expect technical questions related to deploying production-ready ML pipelines and using cloud platforms like AWS, GCP, or Azure. Brush up on your knowledge of MLOps practices and tools like Docker and Airflow.
✨Communicate Effectively
Great communication skills are vital for this role. Practice explaining complex technical concepts in simple terms, as you'll need to collaborate with both technical and non-technical team members.
