Machine Learning Engineer
- Posted 3 months ago
- Be among the first 10 applicants
Job Description
Responsive is looking for an ML Engineer with a strong background in Python, NLP, structured and unstructured data, and basic understanding of ML and DL algorithms/frameworks. The ideal candidate will have a Bachelor's degree in any quantitative discipline, such as Engineering, Computer Science, IT, or Statistics. The ML Engineer should be familiar with Linux and Git and have strong problem-solving and analytical skills. Additionally, the candidate should have a good understanding of mathematics.
Essential Responsibilities
- To develop and implement ML models and algorithms that improve the company's products and services.
- To Work with large datasets to analyze, model, and interpret data.
- To create and optimize NLP models to extract meaningful insights from unstructured text data.
- To collaborate with cross-functional teams to identify and solve complex business problems.
- To continuously monitor and improve the performance of ML models.
- To develop and maintain ML codebase, including version control using Git.
Education
Bachelor's degree in any quantitative discipline, such as Engineering, Computer Science, IT, or Statistics.
Experience
- 4-6 years of experience in Machine Learning
- Proficiency in Python is a must
Knowledge, Ability & Skills
- Comfortable with NLP techniques.
- Basic understanding of ML and DL algorithms/frameworks.
- Familiarity with Linux and Git.
- Good problem-solving and analytical skills.
- Good understanding of mathematics.
More Info
About Company
Skills:
Tensorflow, Machine Learning, Pytorch, Opencv, Python, Ocr, Deep Learning, GenAI, LLMs, PIL
Skills:
Machine Learning, Sql, Spark, Python, Neural architectures, ML libraries, Regression, Gradient-boosted trees, ranking, Classification, Causal reasoning, Evaluation frameworks
Skills:
Github, Sql, Git, MLops, Docker, Databricks, Kubernetes, Python, Orchestration, Testing, Prefect, R, GitHub Actions, CI/CD pipelines, GitOps, Production Monitoring, Software engineering best practices, Model versioning, Containerisation, Unity Catalog, Lineage
Skills:
Machine Learning, Kafka, Sql, MLops, Docker, Spark, Python, Kubernetes, AWS, Ai, anomaly detection, Real-time data processing, Time-series forecasting
Skills:
Github, Jira, Git, Grc, Containers, Release Engineering, CI-CD integrations, SBOM, credential management, diff-based scanning, fingerprinting, secrets scanning, ASPM tooling, RAG retrieval systems, signed builds, SCA, KEV, EPSS feeds, tree-sitter code parsing, Model runtime prompt engineering, GitLab automation, observability tracing