Generative AI Engineer
Turing • India, United States
Education
Bachelor's
Type
Hourly
Listed
24d ago
Apply opens Turing in a new tab.
Apply Now → ⚡ Boost your chances - Optimize your resume with Rezi.aiAbout this role
From the Turing listing
Job Title: Generative AI Engineer For all roles India they want candidates who are ready to RTO. (Report to Office )
- 3 days a week with 4 hours overlap with US till 11pm IST
- On office reporting days it would mean they can leave office a bit early to make that 4 hour overlap with US
- On other 2 days remote work timing 1pm to 11pm IST Employment Type: Full Time Experience Level: Senior
About the Role
We are seeking a highly skilled and motivated Generative AI Engineer to design, develop, and deploy cutting-edge AI solutions leveraging Large Language Models (LLMs), multimodal transformers, and generative algorithms. You will be working on innovative applications across content creation, chat interfaces, autonomous agents, and intelligent data synthesis. This is a high-impact role where your work will help shape next-generation AI capabilities.
Key Responsibilities
- Develop and fine-tune LLMs (e.g., GPT, LLaMA, Mistral, Claude) for custom downstream tasks.
- Implement and optimize RAG (Retrieval-Augmented Generation) pipelines using tools like LangChain, LlamaIndex, or Haystack.
- Build end-to-end Generative AI applications for text, code, images, and audio.
- Leverage vector databases (e.g., FAISS, Pinecone, Weaviate, Qdrant) for embedding-based retrieval.
- Integrate APIs from foundation models (OpenAI, Anthropic, Cohere, HuggingFace, etc.) into product workflows.
- Work with multi-modal models and techniques (e.g., CLIP, DALL·E, Stable Diffusion, Gemini, etc.).
- Optimize model performance, latency, and scalability in production environments.
- Collaborate cross-functionally with ML, data, and product teams to identify and implement use cases.
- Stay up-to-date with state-of-the-art advancements in generative AI and apply them proactively.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field.
- Experience in ML/AI engineering and strong experience with generative AI or LLMs.
- Proficiency in Python, with experience using libraries like Transformers (HuggingFace), LangChain, PyTorch, or TensorFlow.
- Strong understanding of NLP, deep learning, and transformer architectures.
- Experience building scalable ML pipelines and deploying models to production (Docker, Kubernetes, etc.).
- Familiarity with prompt engineering, fine-tuning, and model evaluation techniques.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field.
- Experience in ML/AI engineering and strong experience with generative AI or LLMs.
- Proficiency in Python, with experience using libraries like Transformers (HuggingFace), LangChain, PyTorch, or TensorFlow.
- Strong understanding of NLP, deep learning, and transformer architectures.
- Experience building scalable ML pipelines and deploying models to production (Docker, Kubernetes, etc.).
- Familiarity with prompt engineering, fine-tuning, and model evaluation techniques.
- Must be eligible to work in one of: India, United States
How long hiring takes
Across the AI training platforms we refer candidates to, the median gap between referral and hire is about 30 days. It varies by platform and role, so treat it as a rough guide for this one.
Interview Prep
Sample questions for a AI Engineer role, written in-house to help you prepare.
How do you decide which evaluation metric to optimize for a classification model when the classes are imbalanced?
Accuracy is misleading on imbalanced data because a model can score well by always predicting the majority class. I look at precision, recall, and F1 for the minority class specifically, and pick the metric that matches the real cost of false positives versus false negatives in the deployment context, since those costs are rarely symmetric in practice.
What is your process for debugging a deep learning model that trains fine but performs poorly at inference time?
I start by checking for a train/inference mismatch: different preprocessing, batch normalization behaving differently in eval mode, or data leakage during training that inflated validation scores. Comparing the exact input pipeline used at training time against the one used at inference usually surfaces the discrepancy before I need to touch the model architecture itself.
How do you approach feature selection when working with high-dimensional tabular data?
I start with correlation and mutual information analysis to drop obviously redundant features, then use a tree-based model's feature importance as a first pass filter. From there, recursive feature elimination with cross-validation tells me where the marginal value of additional features drops off, which keeps the final feature set both smaller and more robust to overfitting.
Explain how you would detect and address data drift in a production machine learning pipeline.
I monitor the statistical distribution of input features and model outputs over time, using something like population stability index or KL divergence against a reference window. When drift crosses a threshold, I retrain on recent data rather than the full historical set, and I keep an alert in place so drift is caught before it shows up as a quality regression.
This listing calls for this tool directly. Prep for the technical screen:
What to Expect
Looking at Turing Software Engineering listings we've tracked, contracts in this domain typically run about 8.4 weeks. Actual length varies by project, but this gives you a realistic baseline going in.
Based on 28 extracted Turing Software Engineering listings.
Why this role
We are seeking a highly skilled and motivated Generative AI Engineer to design, develop, and deploy cutting-edge AI solutions leveraging Large Language Models (LLMs), multimodal transformers, and generative algorithms. You will be working on innovative applications across content creation, chat interfaces, autonomous agents, and intelligent data sy
Skills and categories
Explore other opportunities in related specializations:
Related jobs
Browse All Jobs from Turing
Discover more opportunities on Turing that match your skills and interests.
View All Turing Jobs →Verified Reviews
Community Reviews
Share your experience with Turing
Help other candidates make better decisions by leaving a review.
Sign in to leave a reviewLeave your review
Common questions
How and when does Turing pay contractors?
Monthly, in USD, via Deel, Payoneer, or direct bank transfer. You're engaged as an independent contractor responsible for your own local taxes. Plan your cash flow around a monthly cycle if you're used to weekly payouts elsewhere.
Do I need to be a software engineer to work for Turing?
No, not anymore. Turing built its name matching senior engineers with Silicon Valley companies, but it has since expanded into AGI infrastructure work and now hires non-engineering domain experts, technical writers, and researchers for post-training data annotation and RLHF. A strong analytical background and excellent English matter more than coding ability.
What does task-based AI training work look like?
Practical, hands-on data work: recording short videos, categorizing images, rating text responses, or analyzing data. Tasks are designed to be short and distinct, typically 5 to 60 minutes each.
What does asynchronous AI training work mean in practice?
No set hours, no check-ins, no meetings. You log in when you want, pick up an available task, complete it, and submit; nobody is waiting on you in real time. That's different from remote employment, where you're expected online during business hours. The tradeoff: you're competing with others for available tasks, so an empty queue means there's simply nothing to do until more work is released.
What does Software Engineering work look like for a Generative AI Engineer?
Tasks here are scoped to Software Engineering, not generic labeling. As a Generative AI Engineer, expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to Software Engineering) rather than following a one-size-fits-all rubric. If you don't have hands-on Software Engineering background, this is likely not the right listing to start with.
What specific skills does this listing call for?
Coding and Python are named directly in the listing. If you don't have hands-on experience with these, expect the screening process to test for them directly rather than accepting adjacent experience as a substitute.
How much does this specific role pay?
The listing doesn't state a rate. The $25–$55/hr shown here is our estimate from the role type and location (see /pay-methodology), so treat it as a rough guide and confirm the actual rate with the platform before committing time.
What happens when I click Apply on this listing?
You'll be taken to Turing's external site to complete your application there. This listing links through a referral, but the process is identical to applying directly; the link just routes you correctly. Create an account on their site and follow their onboarding steps.
Can I apply from outside India or the United States?
This specific role is open only to people based in India and the United States. If you are somewhere else, applying is unlikely to lead to an offer even if you pass the assessment, because the restriction is usually about where the work can legally be contracted rather than your skills. Read the full description for any tax-residency or right-to-work caveats before you apply, since they can differ by country.