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About This Role
Sub\-Team
Experience
##### 3\-4
Salary
##### As per industry standard
#### Skills Required
- Experience with production use of OpenAI or comparable LLM platforms.
- Familiarity with embeddings, vector search, semantic retrieval, and RAG workflows.
- Experience with agent\-style workflows, orchestration patterns, multi\-step pipelines, or tool\-calling systems.
- Awareness of recent AI ecosystem developments such as MCP, tools/skills patterns, and evolving agent integration approaches.
- Experience with batch jobs, background workers, schedulers, or queue\-based processing.
- Familiarity with Docker and containerized deployments.
- Exposure to AWS or similar cloud platforms.
- Understanding of AI observability, token usage, and cost\-aware implementation.
- Experience contributing to technical design and solution planning.
#### Description
We are looking for an AI Developer to build and maintain AI\-powered products and services. This role requires strong hands\-on ability across LLM applications, backend development, data handling, and practical AI implementation.
The ideal candidate should be able to take requirements, design workable solutions, and deliver production\-ready features. They should also have a solid understanding of broader AI concepts beyond prompt engineering, including model training fundamentals, data science basics, and awareness of newer developments in the AI ecosystem.
Key Responsibilities:
- Design and implement AI\-powered product features using modern AI and LLM\-based approaches.
- Build and maintain backend AI services and APIs using Python and FastAPI.
- Familiarity with tensorflow/pyTorch and huggingface ecosystem.
- Develop prompt workflows for structured, reliable, and high\-quality outputs.
- Build workflows involving tool use, orchestration, validation, retries, and agent\-style execution.
- Integrate AI features with application backends, databases, internal services, and external APIs.
- Work on use cases such as summarization, search, retrieval, document Q\&A, workflow automation, and chatbot\-style systems.
- Prepare and process data for AI use cases, including cleaning, chunking, transformation, labeling, and metadata handling.
- Work with PostgreSQL or similar relational databases for storage, retrieval, and AI\-related application logic.
- Support model\-related tasks such as dataset preparation, fine\-tuning workflows, evaluation, and training pipeline support where needed.
- Improve AI quality through prompt refinement, testing, guardrails, and evaluation methods.
- Keep up with relevant AI developments, frameworks, and emerging patterns such as agent ecosystems, MCP, tools/skills\-based architectures, and related integration standards.
- Monitor and troubleshoot AI systems for quality, latency, failures, and cost.
- Collaborate with product, backend, and frontend teams to ship end\-to\-end features.
- Document implementations clearly and follow maintainable engineering practices.
Preferred Qualifications :
Experience with production use of OpenAI or comparable LLM platforms.
- Familiarity with embeddings, vector search, semantic retrieval, and RAG workflows.
- Experience with agent\-style workflows, orchestration patterns, multi\-step pipelines, or tool\-calling systems.
- Awareness of recent AI ecosystem developments such as MCP, tools/skills patterns, and evolving agent integration approaches.
- Experience with batch jobs, background workers, schedulers, or queue\-based processing.
- Familiarity with Docker and containerized deployments.
- Exposure to AWS or similar cloud platforms.
- Understanding of AI observability, token usage, and cost\-aware implementation.
- Experience contributing to technical design and solution planning.
#### Employment Type
Permanent
#### No. Of Positions
1
Job Title
##### Infrastructure Engineer
Sub\-Team
Experience
##### 4 \-10 (Contract)
Salary
##### As per industry standard
#### Skills Required
Nice to Have Experience with:
Microsoft Dynamics CRM (on\-prem)
Legacy .NET Framework applications
Distributed task or job processing systems
AI/ML–adjacent platforms (search, ingestion, chat, data pipelines)
ISO 27001 or other compliance\-driven environments
#### Description
4\-10 years in infrastructure, systems, or platform engineering roles
Proven experience operating polyglot production environments, including:
Windows Server–based workloads (IIS, SQL Server, legacy .NET Framework applications)
Linux\-based workloads (container hosts, automation, integration, and service platforms)
Deep experience with:
Microsoft Azure (VM\-centric architectures and hybrid workloads) \- VNets, subnets, routing, NSGs, NAT Gateways, Public IPs, VPN Gateways (P2S \& S2S), Private DNS zones and internal name resolution.
Windows Server \& IIS – Hosting, App pools, bindings, TLS configuration, URL Rewrite, App Pool, Troubleshooting.
Microsoft SQL Server – indexing, performance troubleshooting, Disk layout and host caching considerations, Backups, restores, maintenance plans.
Hands\-on experience supporting containerized applications (Docker) on Linux VMs
Strong troubleshooting instincts across application, OS, network, and cloud boundaries
Comfortable operating legacy enterprise systems while incrementally modernizing architecture and workflows.Strong networking fundamentals (DNS, routing, NAT, VPNs, firewalls)
Operate and troubleshoot the custom Distributed Task Platform
Enforce security best practices across infrastructure
Maintain and evolve monitoring and alerting
Manage and respond to infrastructure\-related tickets in Freshdesk
Proficiency with CLI\-driven workflows and automation tools:
Azure CLI
PowerShell
Bash
Python
Operational
Able to operate independently during on\-call shifts across a global time\-zone model
Calm, methodical incident response under pressure
Clear written and verbal communication, including incident updates and postmortems
Comfortable collaborating with distributed teams
#### Employment Type
Contract (duration: not specified)
#### No. Of Positions
2
Job Title
##### .Net Developer
Sub\-Team
Experience
##### 1\-2
Salary
##### As per industry standard
#### Skills Required
C\#, ASP.Net Core, ASP.NET MVC, Web API, SQL Server, Entity Framework, HTML5, CSS
#### Description
- Well\-versed in developing .NET applications using C\# with best practices.
- Experience in creating complex queries, tables, stored procedures, and views in SQL Server.
- Involved in end\-to\-end implementation of .net applications in an agile environment.
- Experience developing applications using Git.
- Strong architectural and design skills with the ability to formulate solutions based on client requirements.
- Good understanding of Visual Studio IDE.
- Ability to diagnose end\-user problems and prescribe the right solutions using the appropriate combination of tools and technologies.
- Comprehensive understanding of object\-oriented and service\-oriented application development techniques and theories.
- Excellent communication skills, both oral and written.
#### Employment Type
Permanent
#### No. Of Positions
4
We have flexible hours, enough time off, and breathtaking events. A healthy work\-life balance is valued here.
Deliver excellence from anywhere you want. You won’t be penalized for operating out of office.
23 days of work. 8 holidays. It’s time to take a vacation, pursue your favourite hobby or time with family \& friends.
Great work requires great tools. If you need something to do the job, we will get it right away for you.
100% coverage of health insurance and quality healthcare initiatives for our employees and their families.
A gym to stay fit, contests to win bucks, events to celebrate, a football ground, a cricket stadium, and what not!
### Best Work: Meaningful, Exciting
At Vofox, your colleagues will include the industry’s biggest thinkers, talented grads, and everyone in between. You’ll work with new technologies and solve original problems. You’ll find that management is approachable, flexibility is accepted, and work\-life balance is promoted.
We also give employees the space to be who they are and the support to become who they want to be.
### Pride: To Be A Vofoxian
There is a lot to be proud of when you have the Vofox “V” on your badge, and our ability to transform how people and companies tell their stories.
Our advantages go beyond compensation and perks to take great care of you. Our programs are designed to enrich your future while giving you more fun.
### Live Well: Healthy, Happy
At Vofox, we know that health is more than doctor visits and life is much more than work. That’s why we go beyond generous medical, dental, and vision benefits for you and your family.
Into yoga or working out with a trainer? You’ll get wellness reimbursements. Feeling stressed? Our employee assistance team is here to help. Best of all, you get healthy snacks and chef\-worthy food in our own cafeteria.
- #### You love a varied
workday
- #### You never back down from
a challenge
- #### You take initiative
- #### You are fundamentally
curious
A Little About Us
---------------------
We pioneered Kochi, the Queen of the Arabian Sea, and have powered world\-changing innovation ever since. Today, we’re advancing AI, automation, IoT, data science, and more to solve humanity’s greatest challenges and make the world healthier, safer, and smarter. Some of the most knowledgeable and hard\-working people in the technology industry work here.
- ### Meaningful Work
You’ll be complemented with competitive compensation \& benefits that enable you to live your best life. Whatever makes you comfortable – we are most certainly not a suit \& tie company.
- ### Exciting Job
With a career with us, you’ll always find a new challenge that excites you. We work with clients from different countries and niches so you have all the chances to tackle interesting problems every time you work with a project.
- ### Smart People
At Vofox, you’ll be working with the best minds in technology. Together, we can build great software. For our highest achievers across all departments – recognition and appreciation from both leadership \& peers.
- ### Work Happier
Vofox is a place where honesty is celebrated, uniqueness encouraged, and you are seen. You will be able to communicate with the client directly, helping us keep our remote\-first culture alive.
Be Seen. Be Yourself. Be Valued.
====================================
Right Environment
---------------------
No matter if you work in the office, remotely, or at a client’s location. We will ensure that we collaborate well and provide you with the right environment and tools to excel at your job.
Virtual
-----------
Great ideas come from anywhere. We're entering a new era of work, one that will see more of our day\-to\-day tasks taking place in a virtual environment, and we're adapting to embrace this change.
Beloved Workplace
---------------------
We are all about infinite opportunities for everyone. Employee satisfaction is a critical success factor in our business. We have been building a place where people love to come to work.
Growth
----------
We encourage you to identify your training goals. Then we help you exceed them. Your path will include on\-the\-job training, trainee programs, and individual coaching from managers.
\#vofox \#vofoxsolutions
----------------------------
Our Hiring Process
----------------------
##### By the end of 2021, Vofox had consolidated its selection process and had received over 10,000 candidate applications, hiring only the Top 1% of IT Talent.
We need people who share our beliefs. This culture has been instrumental to our success and helped us to build a stunning team that thrives in an environment of freedom and responsibility.
Our collaborative interview process provides an opportunity for you to showcase your skills and talents and to help you understand Vofox’s culture. Throughout the hiring process, we encourage you to ask questions about the position and our culture to help determine whether Vofox is right for you.
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At VOFOX SOLUTIONS PVT LTD, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
VOFOX SOLUTIONS PVT LTD AI Hiring
VOFOX SOLUTIONS PVT LTD has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Irving, TX, US.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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