DevOps Lead: 

Top consumer brands like Nestle, Kimberly Clark, Natures Bounty, Johnson & Johnson, Mondelez, Kellogg to name a few rely on CommerceIQ suite of products to make efficient business decisions on a daily basis. It is critical to have services which run high quality data and algorithms that drive business decisions for our customers in a timely manner. As a DevOps you are responsible for building scalable, extensible, secure infrastructure on cloud for CommerceIQ’s applications and data science teams. 

In this role, you will work with a couple of Infra/DevOps SDEs and partner with engineering managers to achieve CommerceIQ’s QoQ goals. As a DevOps lead, you will play a crucial role in upkeep security, cost, deployment infrastructure and maintain/develop services owned by Infra/DevOps team.

A successful candidate will be obsessed with technology and relentlessly raise the bar on the architecture, design and quality of code delivered while aggressively pursuing optimizations to meet cost and scale SLAs. The candidate should be capable of managing a fast-paced delivery schedule and influence and drive a high-level engineering strategy with the leadership, as well as take a hands-on approach to implementing that strategy.

Functional level Expectations

• You should possess advanced knowledge of AWS and other software design approaches to guide the DevOps team in designing infrastructure that caters to scale, concurrency. Preferably AWS certified.
• You should be able to work in situations where you can use your prior expertise and judgment to determine goals, identify constraints, and propose an actionable plan. 
• Your work is typically focused on working with multiple teams’ architecture and product solutions. 
• You should be able to lead the design and implementation that are extensible and scalable
• For continuous integration and deployment
• For multi cloud deployments
• For DR of various services with CiQ infrastructure
• You should be able to influence as a “team lead”, management decisions and priorities and actively mentor to create force multipliers
• You should drive teams to adhere to engineering best practices in SDLC like code coverage, acceptance testing, CI/CD and design patterns that ensure consistency and standardization of architecture
• You should proactively simplify code, identify bottlenecks and resolve team architecture deficiencies. 
• You should be able to work along with other SDEs on their team, build relationships with stakeholders including customers, product managers, cross functional partners and external partners and integrate for a cohesive launch. 

Required Skills

• At least 6-10 years of technology experience including 3+ years of working experience in cloud 
• Ideal candidate should have handled operations, deployment and security of multiple SaaS/B2C products
• Deep knowledge of Python, Cloud or GoLang and one of the public clouds
• Good knowledge of log collection designs like EFK and metric collection tools like newrelic, Prometheus/Grafana or SignalFx
• Good knowledge in design, creation and consumption of RESTful API, Micro service architectures on public clouds preferably AWS
• Excellent analytical, communication and coding skills is a must.
• Thorough orientation towards code reviews, coding/design standards and documentation
• Good knowledge in designing with messaging systems such as SQS, Kafka.
• Good knowledge in designing with ETL pipelines using AWS Step, Azkaban, Airflow
• Good knowledge of any big data engine like Spark would be an advantage.

Below is a brief description of the charter for Infra team (subject o product/business deliverables)

Prometheus / Grafana 

K8s metrics and deployment metrics

We use newrelic(NR) for log collection and operational metrics. But certain shortcomings and solved problems in Prometheus/Grafana might force us to move away from NR. Apart from the prometheus track, the lead will have to work with all. stakeholders [apps/DS] to migrate from OCD to K8s, with all balance and checks in place

EFK stack

Log collection and analysis is via newrelic and it’ll cost us as we move more applications to K8s. We need to optimise or explore options like EFK stack of logs or sumo logic etc 

Security audit

We need to be proactive and do frequent security audits of our applications. We need a security center with all our documentation. Place to store the docs/questionnaires we filled for our clients etc. 

BCP 

We need to audit all our services for disaster recovery and develop a BCP across the company.

CI/CD 

The lead is expected to enforce git branching and set code cov, style check guidelines across teams and projects. E.g Publishing the guidelines for Java project, NodeJS project, Python project. Establishing average code cov metrics, running static code analysis, findbug and other security code scanning tools

Infra services

The Infra team also has many services, especially crucial services like BSS (CSS) . These infra services should set the benchmark for DevOps best practices in the org. 

Azkaban

Azkaban is our ETL orchestrator. It's run in-house and has custom code deployed. Maintenance of Azkaban to match growth is needed. Exploration and guidance to use other orchestrators like airflow, step function, astronomer is also expected

AWS admin and access / SF admin and access / AWS/SF cost , unit cost for client

Constant efforts to identify and reduce costs

AWS partnership [case studies, blogs, trainings, tech conf talks]

Cost savings across all our infrastructure.

SOC2 and other compliance 

Automate our soc2 process with diligence. This is more important as we expand to other pillars of soc2 and ISO.

Company Overview

At CommerceIQ, we help consumer brands accelerate their retail ecommerce market share growth and profitability through machine learning algorithms. We are building the world’s most complete and sophisticated Retail Ecommerce Management Platform, which connects and intelligently automates the management of retail ecommerce channels like Amazon, Walmart, and Instacart, across the entire ecommerce operational chain of retail media management, sales operations, supply chain, and digital self analytics.

We are in hyper growth mode, having recently raised our Series D funding at unicorn valuation (>$1B) and ended our third year of triple-digit revenue growth. Continued acceleration of our growth is fueled by landing new customers, expanding our platform through new products, managing new retail ecommerce platforms, and delivering exceptional customer service to unlock high net retention rates.

What You’ll Be Doing

As a Lead ML Engineer in the Data Science team, you will work closely with the engineering, product, and operations teams to build state-of- the-art ML based solutions for B2B SaaS products. This will entail applying advanced ML algorithms at scale for core products and developing robust end to end production pipelines which includes Human-in-the-Loop component to boost the quality. 

In this role, you will find innovative ways to apply emerging technologies to improve business processes and drive more value for customers. The ideal candidate will have a strong background in machine learning model development, natural language processing and understanding, and data analysis which they can utilize to manage and improve our company’s AI/ML initiatives. 

• Architect and Own multiple AI driven end to end pipelines that allows for deployment and scalability of machine learning models
• Build tools and capabilities that help with data ingestion to feature engineering, data management and organization
• Build tools and capabilities for scalability through distributed optimization 
• Deploy  cutting edge algorithms like LLMs etc. on GPUs at scale
• Work with stakeholders on the research and software engineering side of the company to understand how to support their teams
• Build tools and capabilities for model management and model performance monitoring
• Build operating services at scale with high availability and reliability
• Propose and implement the best engineering practices for scaling ML-powered features, with a goal to enable the fast iteration of and efficient experimentation with novel features
• Contribute and influence the ML infrastructure roadmap in collaboration with Data Science team

What we are looking for -

• Bachelor’s or Masters in Computer Science or Maths/Stats from a reputed college with 5+ years of experience in solving of experience in machine learning engineering problems 
• Experience and understanding of the entire machine learning pipeline from data ingestion to production
• Experience with machine learning operations, software engineering, and architecture
• Experience with large-scale systems including parallel computing and GPUs
• Experience architecting and building an AI pipelines that supports productionization of ML models
• Experience with MLOps systems
• Strong programming skills in a scientific computing language such as Python, SQL
• Experience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy
• Experience working with ML tools such as Tensorflow, Keras, and Pytorch
• Ability to take successful, complex research ideas from experimentation to production
• Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
• Good depth and breadth in machine learning (theory and practice), optimization methods, data mining, statistics and linear algebra

Why you will love to work with us -

We have multiple brands, which are among the biggest brands operating on amazon, as our customers. You will be responsible for working with their data and developing models and algorithms to drive lift in tune of hundreds of thousands of dollars.

• Opportunity to work on cutting edge technologies in text and images data like LLMs, OCR, transformer based embeddings models
• Deploy code using the most sophisticated tech stack like AWS, GCP etc.
• You will own projects end to end i.e., from exploration to final production
• You will be empowered to make decisions. It implies more responsibilities but high learning
• Immense opportunities to learn and develop ML based SaaS products for brands and get company-wide recognition
• Forget endless meetings. Get things done and start making an impact from day 1
• Work hard, have amazing fun, create history, build the future of eCommerce 
• Start-up environment with a strong culture and values to accelerate your career 

The Role:

The e.fundamentals Digital Shelf Analytics platform gathers almost 4 million web pages per day from around 500 retailers worldwide. Gathering data on such a massive scale demands specialised tools for scheduling and reviewing thousands of individual tasks.

The Scheduling team is responsible for devising, building and supporting these tools. The team creates applications and services that enable our internal users to manage tasks safely and efficiently at scale. We’re looking for an experienced senior Software Engineer to lead the team as we develop a brand new iteration of our scheduling system to meet the demands of our rapidly growing customer-base.

What You'll Do:

• You will be responsible for the design, coding, documenting, and maintaining high-end computation platform development.
• You will own the architecture and design of some of the most advanced & complex software systems/products in the industry to create a company-wide impact
• You will be involved in continuously upgrading and building new technology skills and methodologies.
• You will be responsible for innovating, researching, proposing, and discussing the design with your peers.
• You must have the ability to take ownership of Modules delivery and lead a team.
• You will be a key member of the hiring panel across CIQ.
• You will be the gatekeeper of the tech decisions of the team and contribute heavily to the tech strategy, working closely with product and design teams.

• 5+ Years in developing in designing and developing complex and scalable software modules.
• The ideal candidate will be an experienced Java developer with exceptional software system design, problem-solving, and object-oriented coding skills.
• Good hands-on experience in data engineering - ETL pipelines, batch, and streaming data processing (Hadoop, Spark, Storm, Kafka, presto, etc), data analytics & reporting - prior experience with optimizing for storage space, compute time, etc
• Strong expertise in concurrency constructs and debugging memory leaks, expert-level skills in object-oriented, low-level class/interface designs.
• Hands-on experience with building high-performance, highly available, and scalable distributed systems, scaling and evolving them.
• Hands-on experience with one of the key cloud providers (AWS, GCP, Azure) for the creation and scaling of large-scale distributed systems (compute, messaging, notifications, caching, data stores, monitoring, CI/CD, etc).
• Exposure to multiple kinds of data storage and retrieval strategies - Relational, Non-relational, Document, Graph, Object, Time Series databases.
• BS or MS in Computer Science/Engineering, Mathematics, Statistics, or a similar degree will be considered

DevOps Lead: 

Top consumer brands like Nestle, Kimberly Clark, Natures Bounty, Johnson & Johnson, Mondelez, Kellogg to name a few rely on CommerceIQ suite of products to make efficient business decisions on a daily basis. It is critical to have services which run high quality data and algorithms that drive business decisions for our customers in a timely manner. As a DevOps you are responsible for building scalable, extensible, secure infrastructure on cloud for CommerceIQ’s applications and data science teams. 

In this role, you will work with a couple of Infra/DevOps SDEs and partner with engineering managers to achieve CommerceIQ’s QoQ goals. As a DevOps lead, you will play a crucial role in upkeep security, cost, deployment infrastructure and maintain/develop services owned by Infra/DevOps team.

A successful candidate will be obsessed with technology and relentlessly raise the bar on the architecture, design and quality of code delivered while aggressively pursuing optimizations to meet cost and scale SLAs. The candidate should be capable of managing a fast-paced delivery schedule and influence and drive a high-level engineering strategy with the leadership, as well as take a hands-on approach to implementing that strategy.

Functional level Expectations

• You should possess advanced knowledge of AWS and other software design approaches to guide the DevOps team in designing infrastructure that caters to scale, concurrency. Preferably AWS certified.
• You should be able to work in situations where you can use your prior expertise and judgment to determine goals, identify constraints, and propose an actionable plan. 
• Your work is typically focused on working with multiple teams’ architecture and product solutions. 
• You should be able to lead the design and implementation that are extensible and scalable
• For continuous integration and deployment
• For multi cloud deployments
• For DR of various services with CiQ infrastructure
• You should be able to influence as a “team lead”, management decisions and priorities and actively mentor to create force multipliers
• You should drive teams to adhere to engineering best practices in SDLC like code coverage, acceptance testing, CI/CD and design patterns that ensure consistency and standardization of architecture
• You should proactively simplify code, identify bottlenecks and resolve team architecture deficiencies. 
• You should be able to work along with other SDEs on their team, build relationships with stakeholders including customers, product managers, cross functional partners and external partners and integrate for a cohesive launch. 

Required Skills

• At least 6-8 years of technology experience including 3+ years of working experience in cloud 
• Ideal candidate should have handled operations, deployment and security of multiple SaaS/B2C products
• Deep knowledge of Python, Cloud or GoLang and one of the public clouds
• Good knowledge of log collection designs like EFK and metric collection tools like newrelic, Prometheus/Grafana or SignalFx
• Good knowledge in design, creation and consumption of RESTful API, Micro service architectures on public clouds preferably AWS
• Excellent analytical, communication and coding skills is a must.
• Thorough orientation towards code reviews, coding/design standards and documentation
• Good knowledge in designing with messaging systems such as SQS, Kafka.
• Good knowledge in designing with ETL pipelines using AWS Step, Azkaban, Airflow
• Good knowledge of any big data engine like Spark would be an advantage.

The Role:

The e.fundamentals Digital Shelf Analytics platform gathers almost 4 million web pages per day from around 500 retailers worldwide. Gathering data on such a massive scale demands specialised tools for scheduling and reviewing thousands of individual tasks.

The Scheduling team is responsible for devising, building and supporting these tools. The team creates applications and services that enable our internal users to manage tasks safely and efficiently at scale. We’re looking for an experienced senior Software Engineer to lead the team as we develop a brand new iteration of our scheduling system to meet the demands of our rapidly growing customer-base.

What You'll Do:

• Lead a team of talented engineers, empowering them to deliver a flexible and highly-scalable scheduling system
• Take responsibility for the health and success of the team; maintain and foster a positive and collaborative culture
• Balance hands-on development alongside team leadership responsibilities
• Participate in critical technical and strategic discussions with stakeholders across the product engineering organisation. Help define and maintain a vision and roadmap for the team
• Be responsible for all aspects of the team’s delivery and development cycle; leading and championing agile processes, and driving continuous improvement
• Collaborate with senior engineers to define a target architecture for the system and identify a route towards its delivery
• Champion the work of the team; ensure its successes are celebrated
• Be an advocate for the individuals within the team. Guide them in their personal development, and help them to grow and maximise their opportunities within CommerceIQ
• Participate in engineering and architecture forums to help build a culture of excellence within the engineering organisation

What You'll Bring:

• Extensive experience of using JavaScript, React and Node to build rich applications and supporting back-end APIs
• A track record of building full-stack products at scale
• A background leading other engineers
• Significant experience working with Linux/Unix
• A strong understanding of web technologies: HTML, DOM, HTTP, and CSS
• A strong understanding of modern coding practices and standards
• Great interpersonal and communications skills
• A passion for delivering quality software

Nice to Haves: 

• Experience with TypeScript
• Experience of building services in the cloud, especially with Google Cloud Platform
• Experience of containerisation using Docker and Kubernetes
• Experience of building infrastructure as code, especially with Terraform
• Knowledge of web-scraping and its challenges
• Data analysis and SQL skills

Customer Success Specialist Profile:

Fueled by our customers and business growth, we’re looking for Customer Success Specialists to run and grow relationships with our customers, ensuring they are successfully adopting the product. 

The goal of our Customer Success Specialist at CommerceIQ is, simply, to help our customers achieve profitable revenue growth using our platform. They do so by partnering with the CommerceIQ Customer Success Team and other cross-functional partners to onboard, train, and provide day-to-day support for our customers. Since we partner with e-commerce sales and marketing operations teams on growing their Amazon business, our Customer Success Specialists need to be skilled at understanding the customer’s business priorities and able to map the product capabilities of CommerceIQ and the Amazon e-commerce platform. 

In this role you will:

• Understand customer needs, to then plan, organize and manage all phases of a joint success plan, then focus on how we use our product to help customers meet those needs.
• Be an expert on the CommerceIQ platform and act as a vital resource for helping with training, questions, and troubleshooting customer issues.
• Managing client’s advertising budget and driving success
• Be a subject matter expert in e-commerce advertising for our customers, guiding them on how to drive growth for our customers.
• Perform deep data analysis to answer the client’s strategic questions, and drive action
• Move the needle with respect to the client’s KPIs and continuously showcase the value of CommerceIQ’s platform throughout the engagement period
• Collaborate with our internal teams to shape new features
• Take ownership of customer service requests through coordinating with the technical support and engineer teams to ensure requests are addressed quickly and with a high level of satisfaction
• Advise our Sales team on upselling & cross-selling opportunities that will help our customers succeed.

Preferred Qualities or Experience:

• Bachelor's degree, preferably in Business, Marketing, Communication, Economics or related field
• 5+ total years of professional work experience 
• 4+ years experience in running media and advertising engagement with customers, in a consulting/agency role
• Experience in managing e-commerce marketing budgets (specifically on Amazon, Walmart, Kroger, Instacart) at well-respected agencies for large enterprise brands
• Experience managing Amazon search (AMS) and display (DSP) marketing budgets in the multi-million dollar range 
• Well versed in Bid and Budget management, content optimization, and promotion planning
• An analytical approach to problem-solving with advanced Excel skills
• Project management experience and ability to anticipate and mitigate risks
• Proven Experience in working with VP, SVP, and C-level executives of enterprise-level companies
• Excellent presentation and communication skills including both oral and written
• Track record of retaining and renewing Enterprise customers in the SaaS space. 

Nice to have:

• Experience working with omnichannel such as Wal-Mart, Instacart, etc..
• Knowledge of Amazon marketing tools (AMS, AMG, AAP, etc)
• Track record of retaining and renewing Enterprise customers in the SaaS space

Personal Traits: 

• Embodies CIQ’s Leadership Principles: Customer Obsession, Think Big, take bets and innovate, Win as a team, Take Ownership and deliver results, Dive Deep, Bias for Action and Learn and be Curious 

Technical Expertise

• Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
• Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
• Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
• Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
• Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.
• Applied Problem-Solving

Mandatory skill -

•  Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.Mandatory skill -
• Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
• Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.

Leadership & Collaboration

• Proven ability to lead and mentor a team of applied scientists and ML engineers, providing technical guidance and fostering innovation.
• Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
• Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.

Other

• Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
• Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.

Education & Experience

• Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field.
• 7+ years of hands-on experience in applied machine learning and data science, with at least 2+ years in a leadership or managerial role.

@CommerceIQ, you will :

• Build agentic AI products and capabilities from the ground up
• Design and deliver fullstack features with a high degree of autonomy
• Convert product requirements into scalable technical solutions across the stack
• Help shape and implement the core architecture of a new product
• Work with cross-functional partners across engineering, product, and go-to-market teams to gather requirements and integrate with the broader CommerceIQ platform
• Write clean, well-tested code and contribute to technical documentation
• Participate in code reviews and help set strong engineering standards for the team
  
  

What you will need

• At least 5 years of professional software engineering experience
• Hands-on experience building and shipping production-grade agentic or generative AI systems in a fullstack setting
• Familiarity with technologies such as Python, Node, React, Postgres, Databricks, and AWS, or comparable stacks
• Ability to independently decompose complex problems and drive solutions to completion
• Strong product sense and experience collaborating effectively with cross-functional partners 
• Comfort working in an early-stage or evolving environment where priorities can change quickly

Technical Expertise

• Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
• Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
• Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
• Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
• Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.
• Applied Problem-Solving

Mandatory skill -

•  Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.Mandatory skill -
• Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
• Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.

Leadership & Collaboration

• Proven ability to lead and mentor a team of applied scientists and ML engineers, providing technical guidance and fostering innovation.
• Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
• Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.

Other

• Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
• Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.

Education & Experience

• Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field.
• 5+ years of hands-on experience in applied machine learning and data science.

The Role:

The e.fundamentals Digital Shelf Analytics platform gathers almost 4 million web pages per day from around 500 retailers worldwide. Gathering data on such a massive scale demands specialised tools for scheduling and reviewing thousands of individual tasks.

The Scheduling team is responsible for devising, building and supporting these tools. The team creates applications and services that enable our internal users to manage tasks safely and efficiently at scale. We’re looking for an experienced senior Software Engineer to lead the team as we develop a brand new iteration of our scheduling system to meet the demands of our rapidly growing customer-base.

What You'll Do:

• Lead a team of talented engineers, empowering them to deliver a flexible and highly-scalable scheduling system
• Take responsibility for the health and success of the team; maintain and foster a positive and collaborative culture
• Balance hands-on development alongside team leadership responsibilities
• Participate in critical technical and strategic discussions with stakeholders across the product engineering organisation. Help define and maintain a vision and roadmap for the team
• Be responsible for all aspects of the team’s delivery and development cycle; leading and championing agile processes, and driving continuous improvement
• Collaborate with senior engineers to define a target architecture for the system and identify a route towards its delivery
• Champion the work of the team; ensure its successes are celebrated
• Be an advocate for the individuals within the team. Guide them in their personal development, and help them to grow and maximise their opportunities within CommerceIQ
• Participate in engineering and architecture forums to help build a culture of excellence within the engineering organisation

What You'll Bring:

• Extensive experience of using JavaScript, React and Node to build rich applications and supporting back-end APIs
• A track record of building full-stack products at scale
• A background leading other engineers
• Significant experience working with Linux/Unix
• A strong understanding of web technologies: HTML, DOM, HTTP, and CSS
• A strong understanding of modern coding practices and standards
• Great interpersonal and communications skills
• A passion for delivering quality software

Nice to Haves: 

• Experience with TypeScript
• Experience of building services in the cloud, especially with Google Cloud Platform
• Experience of containerisation using Docker and Kubernetes
• Experience of building infrastructure as code, especially with Terraform
• Knowledge of web-scraping and its challenges
• Data analysis and SQL skills

Technical Expertise:

• Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
• Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
• Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
• Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
• Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.

Applied Problem-Solving:

• Mandatory skill - Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.
• Mandatory skill - Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
• Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.

Leadership & Collaboration:

• (Preferred) Proven ability to lead and mentor a junior applied scientists and ML engineers, providing technical guidance and fostering innovation.
• Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
• Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.

Education & Experience:

• 3+ years of hands-on experience in applied machine learning and data science with Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field or appropriate experience.
• Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
• Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.