How does swipeandhired work?

You set your target roles, salary floor and locations once. swipeandhired scores matching postings against your profile, drafts tailored application materials with AI, and either lets you swipe to apply, one tap at a time, or runs fully on autopilot. Every application is tracked in your dashboard.

Which ATS platforms does swipeandhired support?

All of them. swipeandhired applies on every applicant tracking system (ATS) employers use, including Workday, SmartRecruiters, Greenhouse, iCIMS, Lever, Ashby, Taleo, SuccessFactors, Oracle Cloud and Jobvite, and on a company's own careers page when it uses none of them. You can also bring any posting yourself by link or pasted text.

Can I cancel my subscription?

Anytime, in one click from the billing portal in Settings. Your plan stays active until the end of the current billing period. No retention calls, no dark patterns.

Is my data used for training AI models?

No. Your resume and application data are processed only to run the service for you, matching, drafting, and submitting applications. We never sell your data. If you bring your own AI provider key, requests go directly to your provider under their terms.

AI/ML Engineer at Maersk, India

AI/ML Engineer at Maersk in India. Full-time. Apply with swipeandhired.

Team/Opportunity:

Data AI/ML (Artificial Intelligence and Machine Learning) Engineering involves the use of algorithms and statistical models to enable systems to analyze data, learn patterns, and make data-driven predictions or decisions without explicit human programming. AI/ML applications leverage vast amounts of data to identify insights, automate processes, and solve complex problems across a wide range of fields, including healthcare, finance, e-commerce, and more. AI/ML processes transform raw data into actionable intelligence, enabling automation, predictive analytics, and intelligent solutions. Data AI/ML combines advanced statistical modeling, computational power, and data engineering to build intelligent systems that can learn, adapt, and automate decisions.

What you will do:

Design, develop, and implement robust, scalable, and optimized machine learning and deep learning models, with the ability to iterate with speed
Write and integrate automated tests alongside models or code to ensure reproducibility, scalability, and alignment with established quality standards
Implement best practices in security, pipeline automation, and error handling using programming and data manipulation tools
Identify and implement the right data-driven approaches to solve ambiguous and open-ended business problems, leveraging data engineering capabilities
Research and implement new models, technologies, and methodologies and integrate these into production systems, ensuring scalability and reliability
Apply creative problem-solving techniques to design innovative tools, develop algorithms and optimized workflows
Independently manage and optimize data solutions, perform A/B testing, evaluate performance and evaluate performance of systems
Understand technical tools and frameworks used by the team, including programming languages, libraries, and platforms and actively support debugging or refining code in projects
Contribute to the design and documentation of AI/ML solutions, clearly detailing methodologies, assumptions, and findings for future reference and cross-team collaboration
Collaborate across teams to develop and implement high-quality, scalable AI/ML solutions that align with business goals, address user needs, and improve performance

Required skills:

Programming: Writing code to manipulate, analyze, and visualize data, often using languages like Python, R, and SQL.
AI & Machine Learning: Creating systems that can perform tasks that typically require human intelligence. Using Machine learning (ML), a subset of AI that uses algorithms to learn from and make predictions based on data.
Data Analysis : Inspecting, cleansing, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making.
Machine Learning Pipelines: Using automated workflows that manage the end-to-end process of training and deploying machine learning models.
Model Deployment: Making a trained machine learning model available for use in production environments.

Specialized Skills:

Big Data Technologies: Using continuous integration and continuous delivery (CI/CD) pipelines to automate the process of software development, including building, testing, and deploying code
Natural Language Processing (NLP): Focusing on the interaction between computers and humans through natural language.
Data Architecture: Designing and structuring of data systems, ensuring that data is stored, managed, and utilized efficiently
Data Processing Frameworks : Using tools and libraries to process large data sets efficiently, such as Apache Hadoop and Apache Spark.
Technical Documentation: Creating and maintaining documentation that explains the functionality, use, and maintenance of software or systems.
Deep Learning: Using a subset of machine learning involving neural networks with many layers, used to model complex patterns in data.
Statistical Analysis: Collecting and analyzing data to identify patterns and trends, and to make informed decisions.
Data Engineering: Designing and building systems for collecting, storing, and analyzing data at scale.

Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.

We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing [email protected] .