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For Companies At a Glance
- Tasks: Lead the development of scalable machine learning systems and mentor your team.
- Company: Join a dynamic company at the forefront of ML innovation.
- Benefits: Enjoy remote work flexibility and opportunities for professional growth.
- Why this job: Shape technical strategy and deliver cutting-edge solutions in a fast-paced environment.
- Qualifications: Advanced Python skills and 7+ years of ML engineering experience required.
- Other info: Experience in financial services and cloud platforms is a plus.
The predicted salary is between 60000 - 84000 £ per year.
Senior ML Engineer
Location: Remote / London / Manchester
The Role:
Lead the development and deployment of scalable machine learning systems, driving innovation and mentoring the team while ensuring technical excellence.
Key Responsibilities:
- Build and deploy ML systems from prototype to production.
- Design and maintain MLOps pipelines for efficient model management.
- Set the technical direction for ML initiatives and guide junior team members.
- Translate business needs into robust technical solutions.
What You’ll Bring:
- Advanced Python skills and experience with ML frameworks (e.g., PyTorch, TensorFlow).
- Deep knowledge of MLOps tools and practices.
- Strong foundation in math, statistics, and machine learning theory.
- Proven ability to deploy ML solutions at scale.
Preferred:
- Advanced degree in a relevant field and 7+ years of ML engineering experience.
- Financial services experience and knowledge of cloud platforms (AWS, GCP, Azure).
Impact:
A senior role shaping technical strategy and delivering cutting-edge solutions in a dynamic environment.
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Machine Learning Engineer employer: Search5point0
Contact Detail:
Search5point0 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Make sure to showcase your experience with deploying ML systems at scale. Highlight specific projects where you've successfully implemented machine learning solutions, especially in a production environment.
✨Tip Number 2
Emphasize your knowledge of MLOps tools and practices. Be prepared to discuss how you've designed and maintained MLOps pipelines in previous roles, as this is crucial for the position.
✨Tip Number 3
Since mentoring is a key part of the role, think about examples where you've guided junior team members or led technical initiatives. This will demonstrate your leadership capabilities.
✨Tip Number 4
If you have experience in financial services or with cloud platforms like AWS, GCP, or Azure, make sure to highlight that. Tailoring your application to include relevant industry experience can set you apart.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the key responsibilities and requirements. Tailor your application to highlight your experience in building and deploying ML systems, as well as your knowledge of MLOps.
Highlight Relevant Experience: In your CV and cover letter, emphasize your advanced Python skills and experience with ML frameworks like PyTorch or TensorFlow. Provide specific examples of projects where you successfully deployed ML solutions at scale.
Showcase Technical Leadership: Since this is a senior role, demonstrate your ability to lead and mentor teams. Include instances where you set technical direction for ML initiatives or guided junior team members in your previous roles.
Tailor Your Application: Customize your cover letter to reflect how your background aligns with the company's needs, especially in financial services and cloud platforms. Mention any relevant advanced degrees or certifications that support your candidacy.
How to prepare for a job interview at Search5point0
✨Showcase Your Technical Expertise
Be prepared to discuss your advanced Python skills and experience with ML frameworks like PyTorch and TensorFlow. Highlight specific projects where you've built and deployed ML systems, emphasizing your role in driving innovation.
✨Demonstrate MLOps Knowledge
Since the role involves designing and maintaining MLOps pipelines, be ready to explain your experience with MLOps tools and practices. Discuss how you've managed model deployment and monitoring in previous roles.
✨Translate Business Needs into Solutions
Prepare examples of how you've successfully translated business requirements into technical solutions. This will show your ability to align ML initiatives with organizational goals, a key aspect of the role.
✨Mentorship and Leadership Experience
As this position involves mentoring junior team members, share your experiences in guiding others. Discuss how you've set technical direction in past projects and fostered a collaborative environment.
