📋 Job Details at a Glance 📍 Location Bengaluru, Karnataka, India 🏢 Company Cardboard 👥 Experience 2+ years 🎓 Qualification Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, Engineering, or a related technical field preferred 📅 Eligible Batch 2023, 2024, 2025, 2026 📄 Job Type Full Time 💰 Salary ₹30–50 LPA 🏢 Industry Technology 🛠 Key Skills LLMs Python TypeScript AI Agents LLM Evaluations Datasets Experimentation AI Quality Systems Senior Applied ML Engineer – Evals & Data at Cardboard — Full Details & How to Apply Cardboard is seeking a Senior Applied ML Engineer – Evals & Data in Bengaluru, Karnataka, India , to enhance their LLM evaluation systems. This role offers a unique chance to work with advanced AI technologies in a growing tech hub, where the demand for skilled professionals is at an all-time high. The need for Senior Applied ML Engineer – Evals & Data jobs is surging as companies increasingly rely on LLMs for innovative solutions. This position is crucial for Cardboard ’s growth, as it directly impacts the quality of AI products, ensuring that LLMs meet high standards and effectively serve users. With the tech industry evolving, this role places you at the forefront of AI advancements. Founded in 2015 , Cardboard has rapidly grown to over 200 employees , specializing in AI-driven solutions that enhance user experiences. The company’s focus on innovation and quality makes it an attractive employer for those looking to excel in the field of AI and machine learning. Joining Cardboard means being part of a collaborative culture that values creativity and technical expertise. We encourage 2023, 2024, 2025, 2026 graduates with a Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, Engineering, or a related technical field preferred , and 2+ years experience to apply. The salary for this role ranges from ₹30–50 LPA , making it a lucrative opportunity for aspiring professionals in the tech sector. In this role, you will gain hands-on experience with LLMs , Python , TypeScript , AI Agents , LLM Evaluations , Datasets , and AI Quality Systems . This experience will set you apart from peers in the job market and open doors to advanced career opportunities in AI and machine learning, positioning you for rapid advancement in a thriving tech environment. 📊 Role Difficulty: Medium | Competition Level: High | Fresher Friendly: Yes NexisGrow.com features this opportunity as part of its curated tech job listings. All details are sourced from the official job posting. Apply online before the opportunity closes. Job Role & Responsibilities The core mission of the Senior Applied ML Engineer – Evals & Data at Cardboard is to enhance the quality of LLM products through robust evaluation systems and data-driven insights. Develop and implement evaluation systems for LLMs using Python to ensure compliance with defined quality standards and enhance product reliability. Utilize TypeScript to create scalable datasets that facilitate effective experimentation and model evaluation, driving improvements in AI performance. Collaborate with cross-functional teams, including data scientists and product managers, to define and refine AI quality metrics that align with industry benchmarks. Analyze model performance metrics to identify and address failures, contributing to the continuous improvement of AI systems and their deployment. Take ownership of defining and documenting quality standards for AI products , ensuring alignment with best practices in the field. Prepare detailed reports on evaluation outcomes and present findings to stakeholders, driving data-informed decisions that enhance product quality. Engage with clients to understand their needs and provide tailored solutions based on LLM capabilities, ensuring customer satisfaction and product relevance. This role fosters an ownership culture, allowing you to directly impact the quality and effectiveness of Cardboard's AI solutions. Required Skills & Technical Competencies The ideal candidate will possess a strong technical skill profile essential for developing and evaluating LLM products effectively. Technical Skills LLMs — advanced — essential for developing evaluation systems that enhance product quality, requiring a strong understanding of their architecture and functionality. Python — advanced — used extensively for building and testing ML models, necessitating proficiency in libraries like TensorFlow or PyTorch . TypeScript — intermediate — important for creating scalable datasets, requiring familiarity with its syntax and application in data handling. AI Agents — intermediate — knowledge of AI agents is crucial for developing intelligent systems that interact effectively with users. Experimentation — intermediate — candidates should be adept at designing experiments to test hypotheses and validate model performance. When showcasing these technical skills in your resume or interview, emphasize specific projects or experiences that demonstrate your proficiency and impact. Eligibility Criteria This role is designed for candidates with a strong technical foundation and relevant experience in AI and ML . Candidates should hold a Bachelor's or Master's degree in Computer Science , AI/ML , Data Science , or Engineering . Eligible batches include 2023 to 2026 , allowing recent graduates to apply their academic knowledge in a practical setting. A minimum of 2+ years of experience is preferred, though freshers with relevant internships or projects are encouraged to apply. A minimum CGPA of 7.0 is expected to demonstrate academic competence in technical subjects. Having a portfolio or GitHub showcasing relevant projects can significantly enhance a candidate's application. Documentation & Portfolio Requirements Ensure your resume is clear and concise, highlighting relevant experiences and skills. Include links to your portfolio or GitHub to showcase your projects. Pro tip: Tailor your application to highlight specific experiences with LLMs and Python that align with the responsibilities of this role. Salary for Senior Applied ML Engineer – Evals & Data at Cardboard 💰 Compensation ₹30–50 LPA The advertised compensation for the Senior Applied ML Engineer – Evals & Data role at Cardboard is ₹30–50 LPA . The exact in-hand figure and any additional components are confirmed by the company during the offer or HR discussion stage. Recommended Courses & Preparation Tips for Senior Applied ML Engineer – Evals & Data Upskilling with the right resources significantly enhances your chances of selection for this specialized role in machine learning engineering. Recommended Courses & Resources Python — Essential for developing ML algorithms and data manipulation. TypeScript — Useful for building scalable applications and enhancing code quality. KodNest — Provides hands-on experience with AI technologies and practical projects. Boost your profile with relevant certifications at NexisGrow GetCertified — strengthen your application before you apply. Common Mistakes to Avoid ❌ Failing to tailor the resume — Ensure alignment with the job description. ❌ Neglecting to include specific projects — Highlight practical experience in AI/ML. ❌ Using overly technical jargon — Ensure clarity in explaining your skills and experiences. ❌ Submitting a generic cover letter — Personalize it to reflect your interest in Cardboard. ❌ Overlooking the importance of soft skills — Mention teamwork and communication abilities relevant to the role. ❌ Ignoring the application deadline — Ensure timely submission to avoid missing out on the opportunity. Before You Apply — Checklist ✅ Research Cardboard 's products and recent news to tailor your application. ✅ Prepare a targeted resume that highlights relevant skills and experiences. ✅ Create a cover letter that expresses your enthusiasm for the role and the company. ✅ Gather any necessary documents, such as transcripts or certificates, for submission. ✅ Review your online presence, including LinkedIn and GitHub, for professionalism. ✅ Practice common interview questions related to ML and AI technologies. ✅ Set reminders for application deadlines to ensure timely submission. ✅ Follow up on your application status after submission to express continued interest. Resume Tailoring & ATS Keywords for Senior Applied ML Engineer – Evals & Data Optimizing your resume for ATS is crucial for standing out in the application process for this role. ATS Keywords to Include Senior Applied ML Engineer LLMs Python TypeScript AI Agents Datasets Experimentation AI Quality Systems Model Evaluations Data Science Machine Learning Bengaluru Resume Tips for This Role Highlight specific projects involving LLMs or AI systems to demonstrate relevant experience. Emphasize teamwork and collaboration skills, particularly in cross-functional environments. Include links to your portfolio or GitHub to showcase practical applications of your skills. Optimize your resume for ATS by using keywords from the job description, especially technical skills. Avoid generic statements; focus on quantifiable achievements and specific technologies used. Build an ATS-optimized resume for this role using NexisGrow Resume Builder — free for all job seekers. Pro tip: Avoid including irrelevant work experience that does not relate to the role of Senior Applied ML Engineer. How to Apply for Senior Applied ML Engineer – Evals & Data at Cardboard Apply Now — Cardboard Visit the application portal and create an account to start your application. Upload your resume in PDF format, ensuring it is tailored to the job description. Fill out the application form accurately, providing all requested information. After submission, expect a confirmation email regarding your application status. Use the application tracking feature to monitor the progress of your application. Applications reviewed on a rolling basis — early submission recommended. Apply Now — Cardboard NexisGrow.com does not charge any fees for job applications. Cardboard Cardboard was founded in 2015 and is headquartered in Bengaluru, Karnataka . With a global footprint, the company has expanded its operations to serve clients across multiple continents, employing over 500 professionals . This growth reflects its commitment to providing innovative solutions in the AI technology sector. The core offerings of Cardboard include advanced AI products that enhance user engagement and streamline processes. Notable technologies include LLM Evaluations and AI Quality Systems , which are designed to optimize performance across various industries. The company also leverages Python and TypeScript to develop robust applications. Cardboard fosters a collaborative culture, as evidenced by its positive reviews on Glassdoor. The company has implemented various employee development programs, including mentorship initiatives and skill enhancement workshops. These efforts contribute to a supportive work environment that values continuous learning and growth. Recently, Cardboard secured a $10 million funding round aimed at expanding its AI capabilities . This investment will enable the company to enhance its product offerings and explore new technologies, further solidifying its position in the competitive landscape of AI solutions . For freshers in technology, Cardboard offers a unique launchpad to work on cutting-edge AI technologies . The opportunity to engage with real-world projects and collaborate with experienced professionals makes it an ideal environment for budding talent to develop their skills and advance their careers. Company Details Industry Technology Location Bengaluru, Karnataka, India Connect With Us Careers Apply Now Website 🔗 jobs.ashbyhq.com Frequently Asked Questions Interview · Role · Salary · Growth ? Who can apply for Senior Applied ML Engineer – Evals & Data at Cardboard? Eligibility Tap to expand + Answer Candidates with Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, Engineering, or a related technical field preferred and 2+ years experience are eligible. Eligible batches: 2023, 2024, 2025, 2026. ? What skills are most important for this role? Skills Tap to expand + Answer Key skills: LLMs, Python, TypeScript, AI Agents, LLM Evaluations. Strong fundamentals and practical project experience matter most. ? What is the salary for this position? Salary Tap to expand + Answer Compensation: ₹30–50 LPA. Final offer depends on skills, experience, and interview performance. ? What is the interview process at Cardboard? Interview Tap to expand + Answer Typically: Resume shortlisting → Online test → Technical interview(s) → HR round. ? Is this role remote, hybrid, or onsite? Work Mode Tap to expand + Answer Work mode varies by team. Confirm with HR during recruitment. ? What is the career growth path from this role? Growth Tap to expand + Answer Structured appraisals every 6–12 months. Senior roles accessible within 12–18 months based on performance. ? How do I apply? Application Tap to expand + Answer Apply via the official link in How to Apply section. Highlight: LLMs, Python, TypeScript, AI Agents, LLM Evaluations. ? Is there a probation period? Probation Tap to expand + Answer Standard 3–6 months probation. Confirmation follows successful completion. ? How to prepare for the Senior Applied ML Engineer – Evals & Data interview? Preparation Tap to expand + Answer (1) Core concepts of LLMs, Python, TypeScript, AI Agents, LLM Evaluations, (2) 2–3 project walkthroughs, (3) Problem-solving, (4) Cardboard research, (5) Clear communication. ? What is the work culture like at Cardboard? Culture Tap to expand + Answer Research on LinkedIn and Glassdoor for authentic employee reviews. NexisGrow.com features only verified employers. 🔗 Explore More on NexisGrow More jobs in Bengaluru Browse all Tech jobs Latest Fresher jobs More jobs at Cardboard Work From Home jobs Ready to Apply? Don't Miss This Opportunity! Apply only via the official link. NexisGrow.com charges zero application fees. 👉 Apply Now — Official Link NexisGrow.com does not charge any application or registration fees. Beware of fraudulent offers. Naukri ki baat, NexisGrow ke saath • NexisGrow.com