AI/ML Engineer
Dallas, TX · On-site
LangChain / LangGraph * NLP or Computer Vision * AWS / Azure / Google Cloud Platform * Docker ... entry level candidates are welcome , provided they have practical AI/ML projects and strong ...
New
AI/ML Engineer
Dallas, TX · On-site
LangChain / LangGraph * NLP or Computer Vision * AWS / Azure / Google Cloud Platform * Docker ... entry level candidates are welcome , provided they have practical AI/ML projects and strong ...
New
Entry Level Langchain Developer information
What are the key skills and qualifications needed to thrive as an entry level Langchain developer?
To thrive as an Entry Level Langchain Developer, you need a solid understanding of Python programming, APIs, and basic concepts in machine learning or natural language processing, often supported by a relevant degree or coursework. Familiarity with the Langchain framework, experience with tools such as OpenAI APIs, and version control systems like Git are typically required. Problem-solving ability, eagerness to learn, and effective communication skills help you collaborate and adapt in evolving technical environments. These skills ensure you can efficiently build and maintain AI-powered applications while contributing positively to team projects.
What are some common challenges faced by entry level Langchain developers when integrating large language models into applications?
As an entry level Langchain developer, you may encounter challenges such as understanding the nuances of prompt engineering, managing token limits, and handling inconsistent model outputs. Collaborating with team members to design effective workflows and debugging issues related to API integration are also common hurdles. Regular communication with product managers and senior developers can help you navigate these challenges, and over time, you'll gain confidence in optimizing model performance and ensuring reliable user experiences.
What is an entry level Langchain developer?
An Entry Level Langchain Developer is a software professional who works with LangChain, an open-source framework designed for building applications with large language models (LLMs). They typically assist in developing, testing, and deploying applications that leverage AI-driven conversation and automation. Entry level developers often work under the guidance of senior engineers, learning to integrate APIs, handle data pipelines, and implement prompt engineering. This role is ideal for those starting their careers in AI development, particularly in natural language processing and generative AI tools.
What is the difference between Entry Level Langchain Developer vs Entry Level Machine Learning Engineer?
| Aspect | Entry Level Langchain Developer | Entry Level Machine Learning Engineer |
|---|---|---|
| Required Credentials | Basic programming skills, familiarity with NLP and APIs | Programming skills, basic understanding of ML algorithms, possibly a degree in CS or related field |
| Work Environment | Tech companies, startups, AI-focused teams | Tech firms, research labs, AI and data science teams |
| Industry Usage | AI development, chatbot and NLP applications | Data analysis, predictive modeling, AI system development |
| Search & Comparison Intent | Understanding roles in NLP and AI development | Exploring entry-level AI and ML career paths |
While both roles involve AI and programming, Entry Level Langchain Developers focus on building NLP applications using Langchain, whereas Entry Level Machine Learning Engineers work on broader ML models and algorithms. The roles share similar entry requirements but differ in their specific focus areas within AI development.
What are the most commonly searched types of Langchain Developer jobs in Texas?
The most popular types of Langchain Developer jobs in Texas are:
What are popular job titles related to Entry Level Langchain Developer jobs in Texas?
For Entry Level Langchain Developer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Entry Level Langchain Developer jobs in Texas look for?
The top searched job categories for Entry Level Langchain Developer jobs in Texas are:
Other
Posted 2 days ago
New
Job description
AI/ML Engineer
Location: Dallas, TX, United States
Job Type: Full-Time
Experience: 0–3 years
Work Authorization: OPT, H-1B, , or other valid US work authorization
We are seeking a motivated AI/ML Engineer to design, develop, train, and deploy machine learning and artificial intelligence solutions. The ideal candidate should have strong programming skills in Python and hands-on experience with machine learning, deep learning, data processing, and modern AI technologies.
Responsibilities- Develop and implement machine learning and deep learning models.
- Perform data preprocessing, feature engineering, model training, and evaluation.
- Build AI/ML solutions using Python and popular ML frameworks.
- Work with structured and unstructured datasets.
- Develop and optimize ML pipelines for model training and deployment.
- Implement predictive models and recommendation/classification systems.
- Work with Generative AI, LLMs, prompt engineering, or RAG-based applications.
- Deploy and monitor ML models in cloud or production environments.
- Collaborate with software engineers and data teams to integrate AI/ML models into applications.
- Write clean, maintainable, and well-tested Python code.
- Analyze model performance and improve accuracy, scalability, and efficiency.
- Python
- Machine Learning
- Deep Learning
- TensorFlow / PyTorch
- Scikit-learn
- NumPy
- Pandas
- SQL
- Data Structures & Algorithms
- Data Preprocessing & Feature Engineering
- Model Training & Evaluation
- REST APIs
- Git
- Generative AI / LLMs
- Prompt Engineering
- RAG
- LangChain / LangGraph
- NLP or Computer Vision
- AWS / Azure / Google Cloud Platform
- Docker
- Kubernetes
- MLflow
- CI/CD
- MLOps
- PySpark
- Master''s degree in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, Data Science, Engineering, Mathematics, or a related technical field.
- Master''s degree preferred.
The ideal candidate has a strong academic background in AI/ML, Computer Science, Data Science, or IT and can demonstrate hands-on experience through internships, academic projects, research, GitHub repositories, or professional experience.
entry level candidates are welcome, provided they have practical AI/ML projects and strong technical fundamentals.