Machine Learning Engineer
Quantiphi is hiring a Machine Learning Engineer to build and optimize agentic AI workflows and RAG systems. The role focuses on developing LLM applications using LangChain, Azure AI services, and advanced prompt engineering. You will collaborate with data teams to build scalable pipelines and implement model monitoring in production. The role requires strong backend architecture skills and proficiency in Python and orchestration frameworks.
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Experience
2+ years
Function
Engineering
Work mode
Onsite, India
Company
Tier 2
What you will work on
Quantiphi is hiring a Machine Learning Engineer to build and optimize agentic AI workflows and RAG systems. The role focuses on developing LLM applications using LangChain, Azure AI services, and advanced prompt engineering. You will collaborate with data teams to build scalable pipelines and implement model monitoring in production. The role requires strong backend architecture skills and proficiency in Python and orchestration frameworks.
TAL's take
Solid tier-2 firm offering a well-defined, technical role in the high-growth AI/LLM engineering space.
The JD provides a highly specific, crisp set of responsibilities and technical requirements relevant to the role.
Salaries at Quantiphi
14.3 LPA average
Based on 54 Grapevine salary entries for Quantiphi.
Engineering
0 - 2 years | L1
6 LPA average
Range: 6 - 6 LPA
Engineering
2 - 4 years | L2
14 LPA average
Range: 12 - 16 LPA
Engineering
4 - 6 years | Sr
17 LPA average
Range: 13 - 22 LPA
Engineering
8 - 10 years | C1
32 LPA average
Range: 32 - 32 LPA
Must haves
- Expertise in LLM Orchestration patterns including ReAct and Chain-of-Thought
- Deep experience with Azure AI services and Azure OpenAI
- Strong background in software architecture and event-driven patterns
- Proficiency in Python, PyTorch, and TensorFlow
- Expert-level knowledge of LangChain, LangGraph, or Haystack
- Experience deploying and monitoring LLMs in production environments
Tools and skills
About the company
Quantiphi is a well-established global AI-first digital engineering firm, fitting the mid-tier criteria.
Posts mentioning Quantiphi
Need help and advice please😭🙏🏻
Hi All, I have recently switched from Accenture to Quantiphi. 6th April was the last working day at Accenture and 13th April was my onboarding with Quantiphi. I have around 5 years of working experience as a data engineer, working with SQL, GCP tools, BigQuery, Cloud Composer, Airflow, SSIS, SSRS. During the interview and the job description that Quantiphi gave was perfectly aligning with my skills. But today was the day I am feeling completely lost and broken with no idea on what to do next. I got the project details today and my task here would be, for a client, for a new geographic location they want to expand their business where Azure or GCP or Azure has limited rules, so Alibaba cloud is what they want to use. Now my task would involve about, whatever services they were using in Azure, those same replicas or other concepts how we can achieve or available in Alibaba, those POCs I need to work with. I was completely blank after hearing this. This is so new to me, although learning is not something that I am running away from, but this is not aligned with my skill set and this is not something a data engineer does. My task was to make raw data consumable and help the leadership team in making data driven decisions. Please do genuinely advise me on the next steps what should I do, whom should I reach out to. I am having a breakdown today and been questioning the choice I made choosing this over General Mills as it was paying less. Atleast a product based company won’t do this. I want someone to talk to. Please please help me out guys😭😭
How is Quantiphi analytics work culture and WLB?
Is it good to join Quantiphi as data engineer from a renowned product based company? How is work culture? Learning and pay?
Rate My Techstack: Potential Data Engineering Roles
I will be using a scale of 10 for better quantification. Python : 7/10 SQL: 7/10 PowerBI: 9/10 ML(Pandas): 6/10 PLSQL: 6/10 Advanced Excel: 8/10 Azure Databricks + DataFactory : Started learning Apache Spark: Started learning Communication skills: 9/10 Prior Work Ex: 1.8yrs as a PLSQL developer (started off as a fresher) + one SAP internship of 4months + one Data analyst internship of 1 month Aspiration : Data Engineering Role 1. Is the above techstack enough to get me a good data engineering role? Will I be able to clear the technical rounds at companies like accenture, IBM etc with this profile? I have heard the barrier to entry for data engineering is higher than that of data analyst. 2. Do I need to learn DSA? 3. What salary range do I fall in with this profile? I seek your honest answer. I feel lost. Also, should I focus more on improving my cloud skills or shall I be more competent with my python skills? Which one would pay me off in a better sense financially? I certainly can not focus on all the tools at once.