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About Baringa Baringa is a global consulting firm that partners with leaders to drive change and create value. With deep industry expertise, and enabled by advanced technology, the firm helps clients to deliver with greater confidence and certainty. With over 2,000 people across the UK, Europe, North America, Asia and Australia, the firm combines global insight with local understanding. The firm works across energy and resources, financial services, government and public sector, consumer products and retail, pharmaceuticals and life sciences, manufacturing, and technology, media and telecoms, with capabilities spanning strategy, transformation and operational excellence – all powered by advanced technology, data, AI and digital innovation. Clients value Baringa’s collaborative approach and the way its teams integrate seamlessly – all working with a shared understanding of what matters most. The firm is known for its kind, curious experts who listen closely and care deeply about client success as they help clients transform energy markets, modernise financial platforms, expand telecoms and digital networks through advanced data analytics, enable digital services in government, and unlock growth in consumer sectors. Certified as a Great Place to Work around the world, Baringa has been recognised by the Financial Times in 22 categories of its UK Leading Management Consultants rankings, and by Forbes for four consecutive years as one of the World’s Best Management Consulting Firms. Our Solutions and AI Lab Team are looking for experienced Machine Learning Engineers to join the team. In SAIL, we build state-of-the-art AI solutions that help our clients with some of their biggest projects - ranging from tools that support energy networks forecast risk and adapt to climate change using empirically-derived resilience models, to image recognition software using satellite and aerial imagery, to genAI-powered applications including bespoke assistants and agents. We are focused on delivering value-adding solutions aligned to our client’s specific needs. This expertise is applied across clients in all of our industry market sectors (Financial Services, Products & Services, Energy & Resources, Pharmaceutical & Lifesciences and Government). Curious what that impact looks like? Check out our ENA AI Platform case study to see how we accelerated low-carbon device roll-outs for the UK. What you will be doing Defining and implementing machine learning projects over the full lifecycle, from conception to data preparation, model engineering, evaluation and deployment and finally model monitoring and maintenance Establishing and developing ML Ops frameworks and standards for clients and embedding within their infrastructure Working with clients to take them on the journey, upskilling along the way and ensuring they are kept in the loop and can take ownership after you roll off the project Performing maturity assessments across clients’ Cloud/AI environments and recommending improvements Building ML strategy blueprints and advising clients on the different technology options Translating business requirements (both functional and non-functional) into solutions, ensuring compliance with the organisations strategy, policies and standards and in some cases, help customers to define new policies, philosophies and standards Helping clients to identify risks and mitigations for their ML and DS programmes, as well as transition from on-prem to modern cloud-based infrastructures (AWS, Azure, GCP) Working with clients in key areas of ML model governance, such as in defining philosophies including fairness, transparency, interpretability, and accountability Your Skills and Experience We are seeking passionate and dynamic ML engineers who are excited by building production ML solutions, and keen to take an active part in the growth of the company. We’re looking for people who can both advise our clients and get hands on in technical delivery to bring a solution to life. Passionate person who is excited by problems within machine learning and can bring a good mix of technical delivery and core consulting skills in client engagements Advanced degree in computer science, mathematics, physics, engineering or related STEM field Strong problem-solving skills and solid grounding in classical ML and deep learning: from applied statistics and traditional machine learning algorithms to transformers and SOTA deep learning Excellent collaboration and communication skills, both with teams and in client-facing engagements Interested in building AI applications, ranging from forecasting tools to image recognition applications and LLM-based chatbots and agents Proven ability to build machine learning models and pipelines using Python and common ML and DL libraries ( e.g. Pytorch, Tensorflow ) from early conceptualisation to full deployment in scalable production environments Ability to design, deploy and maintain ML solutions on modern frameworks to meet functional business requirements, adhering to software engineering best practices and with exposure to version control, testing, MLOps, CI/CD and API design Hands on experience in using one of 3 major cloud technologies ( AWS, Azure or GCP ) in a production environment, as well as ML platforms ( e.g., AWS Sagemaker, Azure Machine Learning studio ) Be a ‘lifelong learner’ and can demonstrate a drive to always be learning and developing your skillsets and develop the skillsets of others around you Join us All applications received will be reviewed by a member of our Talent Acquisition team. We never rely solely on automated screening or AI tools to make hiring decisions. Your application will be considered for employment without regard to race, ethnicity, religion, gender, gender identity or expression, sexual orientation, nationality, disability, age, faith or social background. We do not filter applications by university background and encourage those who have taken alternative educational and career paths to apply. We would like to actively encourage applications from those who identify with less represented and minority groups. We operate an inclusive recruitment process, ensuring reasonable adjustments where needed. Please contact a member of our Recruitment Team to discuss further. Baringa Privacy Notices For UK & EU Your personal data will be retained by Baringa for up to two years, in accordance with our UK Recruitment Privacy Notice / EU Recruitment Privacy Notice , to evaluate your application and meet our legal and reporting obligations. In line with the General Data Protection Regulation (GDPR), you have the right to request access to, rectification, or erasure (subject to legal limitations) of your personal data. For more information, please contact us at privacy@baringa.com For the USA Your personal data may be retained by Baringa for up to two years, as outlined in our Recruitment Privacy Notice (AMER & APAC) , to support the recruitment process and internal reporting requirements. Where applicable, and in accordance with relevant federal and state laws, you may have the right to request access to or correction of your personal information. For further details, please contact privacy@baringa.com For Australia & Singapore Your personal data will be retained by Baringa for up to two years, in accordance with our Recruitment Privacy Notice (AMER & APAC) , to assess your application and meet applicable reporting and legal obligations. In line with the Australian Privacy Act and Singapore’s Personal Data Protection Act (PDPA), you may have rights to access, correct, or request limited deletion of your personal data. For more information, please contact us at privacy@baringa.com
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.