Machine Learning Engineer
Machine Learning Engineer
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INR INR 3500000 - 5000000
1 Vacancy
Job Description
Key Responsibilities:
- Model Development: Conceptualize develop and deploy machine learning models that power our NLP retrieval ranking reasoning dialog and codegeneration systems.
- Algorithm Implementation: Utilize advanced machine learning algorithms including Transformerbased models reinforcement learning ensemble learning and agentbased systems to enhance our AI systems performance.
- Data Analysis: Lead the processing and analysis of large complex datasets (structured semistructured and unstructured) to inform model development.
- Lifecycle Management: Oversee the entire lifecycle of ML model development encompassing problem definition data exploration feature engineering model training validation and deployment.
- Model Validation: Implement A/B testing and other statistical methods to validate model effectiveness ensuring the integrity and robustness of ML solutions through automated testing and validation processes.
- Stakeholder Communication: Clearly articulate the technical aspects and advantages of ML models to both technical and nontechnical stakeholders promoting understanding and adoption.
Ideal Qualifications:
- Educational Background: Master s degree or Ph.D. in Computer Science Machine Learning or a related quantitative field.
- Industry Experience: Proven experience in building and deploying productionlevel machine learning models.
- NLP Expertise: Indepth understanding and handson experience with NLP techniques and frameworks including the training and inference of large language models.
- Advanced Systems Knowledge: Strong grasp of retrieval ranking reinforcement learning and agentbased systems with experience in developing them for largescale applications.
- Technical Proficiency: Proficient in Python and experienced with ML libraries such as TensorFlow or PyTorch.
- Data Skills: Excellent data processing skills (SQL ETL data warehousing) and experience working with largescale data systems.
- MLOps Familiarity: Experience with machine learning model lifecycle management tools and an understanding of MLOps principles and best practices.
- Cloud Knowledge: Familiarity with cloud platforms like GCP or Azure.
- Industry Awareness: Uptodate knowledge of the latest trends in machine learning and AI with the ability to apply this knowledge to practical projects.
- Software Development Acumen: Good understanding of software development principles data structures and algorithms.
- ProblemSolving Skills: Strong analytical skills attention to detail and logical thinking abilities.
- Team Collaboration: Ability to work collaboratively in a fastpaced startup environment.
machine learning,gcp,software development,tensorflow,algorithms,data warehousing,sql,azure,nlp,etl,pytorch,information retrieval,python
Employment Type
Full Time
Company Industry
Key Skills
- Industrial Maintenance
- Machining
- Mechanical Knowledge
- CNC
- Precision Measuring Instruments
- Schematics
- Maintenance
- Hydraulics
- Plastics Injection Molding
- Programmable Logic Controllers
- Manufacturing
- Troubleshooting
