Looking to start your career in Data Engineering and Machine Learning with a global technology company? IBM is hiring for a Data Engineer – Machine Learning role in Gurgaon, Haryana, offering an entry-level opportunity for candidates interested in machine learning, data analysis, algorithms, and AI-driven solutions.
This role is part of IBM Consulting and focuses on applying Machine Learning concepts to real-world business problems. Candidates will work with stakeholders, evaluate algorithms, interpret statistical data, and communicate technical results that can support business decisions.
If you’re searching for IBM Jobs 2026, IBM Data Engineer Jobs, Machine Learning Jobs for Freshers, Data Engineer Jobs in Gurgaon, or Entry Level AI Jobs, this opportunity is worth checking.
IBM Data Engineer – Machine Learning Recruitment 2026 – Overview
| Particulars | Details |
|---|---|
| Company | IBM |
| Job Role | Data Engineer – Machine Learning |
| Job ID | 85974 |
| Location | Gurgaon, Haryana, India |
| Position Type | Entry Level |
| Employment Type | Regular |
| Work Arrangement | Hybrid |
| Education | Bachelor’s Degree |
| Preferred Education | Master’s Degree |
| Work Area | Software Engineering |
| Experience Listed | 5–15 Years* |
| Travel | Up to 20% or 1 day/week |
| Shift | General / Daytime |
* Important: IBM’s page labels the position Entry Level, but the same listing also displays 5–15 years of experience. These details appear inconsistent, so candidates should verify the requirement directly on the official application page before applying. Because apparently even job descriptions occasionally enjoy creating their own plot twists.
Why This IBM Data Engineer Role Is Worth Applying For
A career combining data engineering and Machine Learning can provide exposure to some of the most important areas of modern technology.
In this IBM role, candidates will work with Machine Learning concepts and techniques to address business challenges. The position involves analyzing statistical information, identifying relevant features, selecting suitable algorithms, evaluating model performance, and communicating results to stakeholders.
The role also sits within IBM Consulting, where teams work with organizations across different industries on technology transformation initiatives.
This means the opportunity is not limited to writing code or building models. It also emphasizes understanding business requirements and translating technical findings into useful insights.
About the IBM Data Engineer – Machine Learning Opportunity
The position is based in Gurgaon, Haryana, with a hybrid work arrangement.
According to the provided job description, the role involves applying Machine Learning methodologies to business problems and collaborating with stakeholders to develop solutions.
The main focus areas include:
- Machine Learning
- Data Analysis
- Statistical interpretation
- Algorithm development
- Algorithm evaluation
- Feature identification
- Data visualization
- Technical communication
- Machine Learning implementation
Candidates who enjoy combining analytical thinking with technology may find this role particularly relevant.
Key Responsibilities
1. Develop Machine Learning Solutions
The role requires applying Machine Learning concepts and techniques to address business challenges.
You may be expected to:
- Understand business problems
- Analyze relevant data
- Identify useful features
- Select appropriate Machine Learning approaches
- Develop solutions based on business requirements
The emphasis is on using Machine Learning to generate meaningful business outcomes rather than simply experimenting with models.
2. Evaluate Algorithm Performance
Another important responsibility is evaluating how effectively Machine Learning algorithms perform.
This involves:
- Selecting suitable algorithms
- Applying relevant evaluation metrics
- Comparing model performance
- Understanding whether the solution meets business requirements
- Improving algorithms when necessary
Candidates should therefore have a solid understanding of basic Machine Learning concepts and model evaluation.
3. Analyze Statistical Data
Data analysis is another central component of the role.
Candidates should be comfortable interpreting statistical information and identifying relevant features that can contribute to solution development.
This requires analytical thinking and the ability to understand relationships within datasets.
4. Communicate Machine Learning Results
Technical skills alone are not enough for this position.
The job description specifically mentions communicating Machine Learning results to stakeholders and providing actionable insights that can support business decisions.
This means candidates should be able to explain technical concepts clearly, even when speaking with people who may not have a deep Machine Learning background.
5. Implement Machine Learning Techniques
The role also involves collaborating with stakeholders to determine appropriate Machine Learning methodologies and implement them to create business value.
This gives the position a combination of:
Machine Learning + Data Analysis + Business Understanding + Communication
Required Qualifications
The official listing specifies a Bachelor’s Degree as the required education.
A Master’s Degree is listed as preferred.
For technical and professional expertise, IBM mentions experience or exposure in several areas.
Machine Learning Concepts
Candidates should be familiar with applying Machine Learning concepts to business problems.
This includes:
- Statistical data interpretation
- Feature identification
- Machine Learning methodologies
- Business problem analysis
Algorithm Development
Candidates should understand algorithms and be able to evaluate their performance using appropriate metrics.
Data Analysis
The role requires the ability to interpret statistical data and identify relevant features for solution development.
Machine Learning Implementation
Candidates should have exposure to implementing Machine Learning techniques and collaborating with stakeholders to select appropriate methodologies.
Technical Communication
Candidates should be able to communicate technical results clearly and turn findings into actionable insights.
Preferred Skills
IBM also lists several areas that can strengthen a candidate’s profile.
Advanced Algorithm Development
Experience with more complex algorithms, performance evaluation, and fine-tuning is preferred.
Data Visualization
Exposure to data visualization tools and techniques can help candidates communicate Machine Learning results more effectively.
Specialized Machine Learning Tools
IBM mentions familiarity with specialized Machine Learning technologies, including tools used for areas such as:
- Natural Language Processing
- Computer Vision
Candidates with projects in these areas may be able to demonstrate relevant practical exposure.
Who Should Apply?
Based strictly on the information provided in the IBM listing, the role may be relevant to candidates interested in:
- Data Engineering
- Machine Learning
- Data Analysis
- Artificial Intelligence
- Algorithm Development
- Statistical Analysis
- Data Visualization
- Business Intelligence
- Technology Consulting
The listing identifies the position as Entry Level, making the role potentially attractive to early-career candidates.
However, the listing simultaneously displays 5–15 years of experience, so candidates should not assume that all freshers are eligible. The experience requirement should be confirmed on the official application page before submitting an application.
Skills to Highlight on Your Resume
If your background aligns with this role, consider clearly presenting relevant skills such as:
Technical Skills
- Machine Learning
- Python
- Algorithms
- Data Analysis
- Statistics
- Data Visualization
- Natural Language Processing
- Computer Vision
- Machine Learning Model Evaluation
Analytical Skills
- Feature Selection
- Statistical Analysis
- Problem Solving
- Algorithm Evaluation
- Business Problem Analysis
- Data Interpretation
Professional Skills
- Technical Communication
- Stakeholder Communication
- Collaboration
- Analytical Thinking
- Solution Development
Only include skills you genuinely understand or have demonstrated through projects, coursework, internships, or professional experience. Keyword stuffing is not a career strategy, despite LinkedIn occasionally making it look like one.
Why IBM Consulting Makes This Role Interesting
The position is part of IBM Consulting, where professionals work with clients on business and technology transformation.
According to the supplied listing, IBM Consulting focuses on areas including:
- Hybrid Cloud
- AI
- Technology transformation
- Consulting
- Business solutions
The role is also based within an IBM Consulting Client Innovation Center, where teams provide technical and industry expertise to clients across public and private sectors.
For candidates interested in combining technical work with consulting and client-facing environments, this can be a useful career direction.
Work Arrangement & Job Details
The position is listed as:
🏢 Location: Gurgaon, Haryana
💻 Work Arrangement: Hybrid
⏰ Shift: General / Daytime
💼 Employment: Regular
🎯 Position: Entry Level
✈️ Travel: Up to 20% or 1 day per week
🏷️ Area: Software Engineering
The role is not listed as fully remote.
Application Tips
1. Build a Machine Learning-focused Resume
Put relevant Machine Learning projects, coursework, internships, and technical experience where recruiters can easily see them.
2. Demonstrate Algorithm Knowledge
Don’t simply list “Machine Learning.” Explain projects where you selected algorithms, evaluated their performance, or improved model results.
3. Show Data Analysis Experience
Projects involving statistical analysis, feature engineering, datasets, dashboards, or data interpretation can strengthen your application.
4. Include Visualization Work
If you have worked with data visualization tools, include relevant projects and explain what insights you communicated.
5. Explain Business Impact
Whenever possible, explain what your Machine Learning project actually solved. A model with a clear purpose is more convincing than a collection of fashionable buzzwords.
6. Prepare to Explain Your Projects
Be prepared to discuss:
- Why you selected a particular algorithm
- How you prepared the data
- Which metrics you used
- How you evaluated performance
- What challenges you encountered
- What business problem the project addressed
IBM Data Engineer – Machine Learning Job Summary
🚀 Company: IBM
💼 Role: Data Engineer – Machine Learning
📍 Location: Gurgaon, Haryana
🎓 Education: Bachelor’s Degree required
🎓 Preferred: Master’s Degree
🏢 Work Mode: Hybrid
🎯 Position: Entry Level
🧠 Focus: Machine Learning & Data Engineering
📊 Core Areas: Data Analysis, Algorithms & Statistics
📈 Additional Area: Data Visualization
🤝 Work: Stakeholder Collaboration
✈️ Travel: Up to 20% or 1 day/week
🕘 Shift: General / Daytime
🆔 Job ID: 85974
Final Words
The IBM Data Engineer – Machine Learning Hiring 2026 opportunity is a strong role to investigate if you’re interested in Machine Learning, data analysis, algorithms, and AI-driven business solutions.
The position provides exposure to Machine Learning development, algorithm evaluation, statistical analysis, stakeholder communication, and implementation of Machine Learning techniques. It is also part of IBM Consulting, giving the role a broader technology and business context.
The official listing identifies the position as Entry Level and requires a Bachelor’s Degree, while also displaying 5–15 years of experience elsewhere on the page. Because of this discrepancy, candidates should carefully verify the experience requirement on the official application portal before applying.
If your profile includes relevant Machine Learning projects, algorithm knowledge, data-analysis experience, and strong technical communication skills, this opportunity is worth reviewing.
Apply Now
Important: Apply through the official IBM Careers portal and verify the eligibility criteria shown during the application process.