What are the responsibilities and job description for the AI/ML Engineer position at TALENT Software Services?
- Job Title: AI/ML Engineer
- Location: Minnetonka Mills, MN
- Duration: 6 months
- Experience: 4-6 years
- Primary Focus: Machine Learning, NLP, LLMs, GenAI, MLOps
- Core Skills: Python, TensorFlow, PyTorch, Docker, REST APIs, Databricks
- Build, train, tune, and deploy machine learning models.
- Translate data science experiments and prototypes into scalable, production-ready ML solutions.
- Develop reliable ML services and pipelines for enterprise production environments.
- Translate data science prototypes into production-grade ML services and pipelines.
- Build training and inference code with:
- Reproducibility
- Versioning
- Automated testing
- Implement scalable online and offline model serving.
- Optimize model serving for:
- Batching
- Latency
- Throughput
- Scalability
- Integrate ML lifecycle tooling, including:
- Experiment tracking
- Model registries
- Deployment automation
- Model monitoring
- Collaborate with Data Engineering teams on feature pipelines and data contracts.
- Own production ML health, including:
- Drift detection
- Performance regression
- Rollback strategies
- Incident response
- Experience applying data science techniques in a commercial enterprise environment.
- Strong understanding of:
- Supervised Learning
- Unsupervised Learning
- NLP
- Time-Series Forecasting
- Statistical Analysis
- Experience with large-scale data and production ML workloads.
- Experience with scikit-learn and Databricks.
- Strong analytical, quantitative, problem-solving, and critical-thinking skills.
- 3 years of production experience with NLP, including:
- Transformers
- GPT
- Other modern NLP technologies
- 2-3 years of experience applying LLMs to real-world business problems.
- Hands-on experience with:
- RAG (Retrieval-Augmented Generation)
- Vector Databases
- Embeddings
- Experience using vision and speech models in GenAI applications.
- Experience working with large amounts of data for NLP and LLM solutions.
- 5 years of software engineering experience.
- 2 years of experience shipping ML models to production.
- Strong understanding of MLOps and ML system design.
- Experience with:
- CI/CD
- DevOps
- Model deployment
- Model monitoring
- Model versioning
- Understanding of ML production challenges, including:
- Data leakage
- Training-serving skew
- Model drift
- Performance degradation
- Strong Python development skills.
- Experience with ML frameworks:
- TensorFlow
- PyTorch
- Experience with:
- Docker
- Kubernetes
- REST APIs
- Experience building APIs for machine learning models.
- Experience with scalable model serving and distributed ML workloads.
- Experience with feature stores.
- Experience with model registries.
- Experience with model monitoring platforms.
- GPU optimization experience.
- Distributed training experience.
- Responsible AI toolkits and compliance experience.
- Strong written and verbal communication skills.
- Ability to present detailed technical analyses to broad audiences.
- Organized, self-motivated, and able to work independently.
- Strong analytical and problem-solving abilities.
- AI/ML Engineering
- Python
- TensorFlow
- PyTorch
- NLP
- LLMs
- RAG
- Vector Databases
- Embeddings
- Databricks
- scikit-learn
- Docker
- Kubernetes
- REST APIs
- MLOps
- CI/CD
- Machine Learning
- Natural Language Processing (NLP)
- AI & GenAI - Products & Tools
Salary : $53 - $57