{
    "url": "https://www.spotsalary.com/salary/machine-learning-engineer/pakistan-pk",
    "canonical": "https://www.spotsalary.com/salary/machine-learning-engineer/pakistan-pk",
    "headline": "Machine Learning Engineer Salary in Pakistan",
    "description": "Median Machine Learning Engineer salary in Pakistan is ₨15.5M per year. Compare P10–P90 salary bands by experience, take-home pay and a five-year outlook.",
    "occupation": {
        "name": "Machine Learning Engineer",
        "slug": "machine-learning-engineer",
        "family": "technology",
        "soc_code": "15-2051",
        "aliases": [
            "ML Engineer",
            "AI Engineer"
        ],
        "description": null
    },
    "location": {
        "name": "Pakistan",
        "slug": "pakistan-pk",
        "type": "country",
        "iso2": "PK",
        "currency": "PKR"
    },
    "period": 2026,
    "confidence": 58,
    "status": "published",
    "method": "nearest_neighbor",
    "updated_at": "2026-10-30T15:10:38+00:00",
    "salary_bands": [
        {
            "level": "entry",
            "years_experience": [
                0,
                2
            ],
            "p10": 5382937.92,
            "p25": 6346344.92,
            "p50": 7516422.28,
            "p75": 8518549.54,
            "p90": 9742147.41,
            "base_share": 95,
            "bonus_share": 5,
            "equity_share": 0
        },
        {
            "level": "mid",
            "years_experience": [
                3,
                5
            ],
            "p10": 8412541.2,
            "p25": 11292583.87,
            "p50": 15452324.41,
            "p75": 19725960.45,
            "p90": 22279634.16,
            "base_share": 88,
            "bonus_share": 8,
            "equity_share": 4
        },
        {
            "level": "senior",
            "years_experience": [
                6,
                9
            ],
            "p10": 17117021.57,
            "p25": 20784955.21,
            "p50": 24452889.61,
            "p75": 28120823,
            "p90": 33011400.02,
            "base_share": 80,
            "bonus_share": 10,
            "equity_share": 10
        },
        {
            "level": "executive",
            "years_experience": [
                10,
                15
            ],
            "p10": 21218002.74,
            "p25": 25764717.61,
            "p50": 30311431.98,
            "p75": 34858146.86,
            "p90": 40920433.35,
            "base_share": 65,
            "bonus_share": 15,
            "equity_share": 20
        }
    ],
    "take_home": {
        "currency": "PKR",
        "tax_rate": 29.69982652273348,
        "top_rate": null,
        "method": "progressive",
        "label": "progressive brackets",
        "standard_deduction": 0,
        "rebate": 0,
        "source": "FBR (Finance Act 2025, salaried)",
        "source_url": "https://www.fbr.gov.pk/",
        "retrieved_at": "2026-10-23T00:00:00.000000Z",
        "verified": true,
        "notes": "Salaried slabs; 0% up to PKR 600,000; 35% only above PKR 4,100,000",
        "bands": [
            {
                "level": "entry",
                "gross": 7516422.28,
                "taxable": 7516422.28,
                "tax": 1811747.798,
                "effective_rate": 24.10385859800309,
                "net_annual": 5704674.482000001,
                "net_monthly": 475389.54016666673,
                "method": "progressive",
                "top_rate": null,
                "standard_deduction": 0,
                "rebate": 0,
                "source": "FBR (Finance Act 2025, salaried)",
                "source_url": "https://www.fbr.gov.pk/",
                "retrieved_at": "2026-10-23T00:00:00.000000Z",
                "verified": true,
                "notes": "Salaried slabs; 0% up to PKR 600,000; 35% only above PKR 4,100,000"
            },
            {
                "level": "mid",
                "gross": 15452324.41,
                "taxable": 15452324.41,
                "tax": 4589313.5435,
                "effective_rate": 29.69982652273348,
                "net_annual": 10863010.866500001,
                "net_monthly": 905250.9055416668,
                "method": "progressive",
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                "standard_deduction": 0,
                "rebate": 0,
                "source": "FBR (Finance Act 2025, salaried)",
                "source_url": "https://www.fbr.gov.pk/",
                "retrieved_at": "2026-10-23T00:00:00.000000Z",
                "verified": true,
                "notes": "Salaried slabs; 0% up to PKR 600,000; 35% only above PKR 4,100,000"
            },
            {
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                "rebate": 0,
                "source": "FBR (Finance Act 2025, salaried)",
                "source_url": "https://www.fbr.gov.pk/",
                "retrieved_at": "2026-10-23T00:00:00.000000Z",
                "verified": true,
                "notes": "Salaried slabs; 0% up to PKR 600,000; 35% only above PKR 4,100,000"
            },
            {
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                "tax": 9790001.193,
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                "net_monthly": 1710119.2322500001,
                "method": "progressive",
                "top_rate": null,
                "standard_deduction": 0,
                "rebate": 0,
                "source": "FBR (Finance Act 2025, salaried)",
                "source_url": "https://www.fbr.gov.pk/",
                "retrieved_at": "2026-10-23T00:00:00.000000Z",
                "verified": true,
                "notes": "Salaried slabs; 0% up to PKR 600,000; 35% only above PKR 4,100,000"
            }
        ]
    },
    "outlook": {
        "direction": "growing",
        "inflation_pct": 7,
        "real_growth_pct": 13,
        "forecasts": [
            {
                "year": 2027,
                "scenario": "base",
                "p25": 17356050.78,
                "p50": 18542789.29,
                "p75": 19729527.81,
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                "drivers": [
                    {
                        "name": "Inflation (CPI)",
                        "note": "7.0% annual price growth",
                        "weight": "high",
                        "direction": "up"
                    },
                    {
                        "name": "Wage growth",
                        "note": "8.0% nominal wage trend",
                        "weight": "high",
                        "direction": "up"
                    },
                    {
                        "name": "Role demand trend",
                        "note": "10.0% annual role demand",
                        "weight": "high",
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                    },
                    {
                        "name": "Hiring demand",
                        "note": "Demand index 58/100",
                        "weight": "medium",
                        "direction": "up"
                    },
                    {
                        "name": "Automation exposure",
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                    {
                        "name": "Real wage growth",
                        "note": "13.0% after 7.0% inflation",
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                    },
                    {
                        "name": "Scenario growth",
                        "note": "20.0% modelled nominal growth",
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                        "direction": "up"
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                ]
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            {
                "year": 2027,
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                "p25": 17139100.14,
                "p50": 18311004.43,
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                "drivers": [
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                        "name": "Inflation (CPI)",
                        "note": "7.0% annual price growth",
                        "weight": "high",
                        "direction": "up"
                    },
                    {
                        "name": "Wage growth",
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                        "weight": "high",
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                        "name": "Role demand trend",
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                        "name": "Hiring demand",
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                        "weight": "medium",
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                    },
                    {
                        "name": "Automation exposure",
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                    {
                        "name": "Real wage growth",
                        "note": "13.0% after 7.0% inflation",
                        "weight": "high",
                        "direction": "up"
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                    {
                        "name": "Scenario growth",
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                        "weight": "high",
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                ]
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            {
                "year": 2027,
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                "drivers": [
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                        "name": "Inflation (CPI)",
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                    {
                        "name": "Wage growth",
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                        "weight": "high",
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                        "name": "Role demand trend",
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                        "name": "Hiring demand",
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                        "weight": "medium",
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                    {
                        "name": "Real wage growth",
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                "year": 2029,
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                        "name": "Inflation (CPI)",
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                    {
                        "name": "Wage growth",
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                        "weight": "high",
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                        "name": "Role demand trend",
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                        "weight": "high",
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                        "name": "Hiring demand",
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                        "weight": "medium",
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                        "name": "Automation exposure",
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                        "weight": "high",
                        "direction": "steady"
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                    {
                        "name": "Real wage growth",
                        "note": "13.0% after 7.0% inflation",
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                    {
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                "year": 2029,
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                "drivers": [
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                        "name": "Inflation (CPI)",
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                        "weight": "high",
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                        "name": "Role demand trend",
                        "note": "10.0% annual role demand",
                        "weight": "high",
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                        "name": "Hiring demand",
                        "note": "Demand index 58/100",
                        "weight": "medium",
                        "direction": "up"
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                        "name": "Automation exposure",
                        "note": "20% exposure",
                        "weight": "high",
                        "direction": "steady"
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                    {
                        "name": "Real wage growth",
                        "note": "13.0% after 7.0% inflation",
                        "weight": "high",
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                    {
                        "name": "Scenario growth",
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                ]
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            {
                "year": 2029,
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                "p25": 25719980.04,
                "p50": 27715495.74,
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                "confidence": 40,
                "drivers": [
                    {
                        "name": "Inflation (CPI)",
                        "note": "7.0% annual price growth",
                        "weight": "high",
                        "direction": "up"
                    },
                    {
                        "name": "Wage growth",
                        "note": "8.0% nominal wage trend",
                        "weight": "high",
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                        "name": "Role demand trend",
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                        "name": "Hiring demand",
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                        "weight": "medium",
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                        "name": "Automation exposure",
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                        "weight": "high",
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                    {
                        "name": "Real wage growth",
                        "note": "13.0% after 7.0% inflation",
                        "weight": "high",
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                    {
                        "name": "Scenario growth",
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            {
                "year": 2031,
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                "drivers": [
                    {
                        "name": "Inflation (CPI)",
                        "note": "7.0% annual price growth",
                        "weight": "high",
                        "direction": "up"
                    },
                    {
                        "name": "Wage growth",
                        "note": "8.0% nominal wage trend",
                        "weight": "high",
                        "direction": "up"
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                        "name": "Role demand trend",
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                        "note": "Demand index 58/100",
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                        "name": "Automation exposure",
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                    {
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                    {
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                "year": 2031,
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                        "name": "Inflation (CPI)",
                        "note": "7.0% annual price growth",
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                    },
                    {
                        "name": "Wage growth",
                        "note": "8.0% nominal wage trend",
                        "weight": "high",
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                    {
                        "name": "Role demand trend",
                        "note": "10.0% annual role demand",
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                        "name": "Hiring demand",
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                    {
                        "name": "Scenario growth",
                        "note": "20.0% modelled nominal growth",
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            {
                "year": 2031,
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                "drivers": [
                    {
                        "name": "Inflation (CPI)",
                        "note": "7.0% annual price growth",
                        "weight": "high",
                        "direction": "up"
                    },
                    {
                        "name": "Wage growth",
                        "note": "8.0% nominal wage trend",
                        "weight": "high",
                        "direction": "up"
                    },
                    {
                        "name": "Role demand trend",
                        "note": "10.0% annual role demand",
                        "weight": "high",
                        "direction": "up"
                    },
                    {
                        "name": "Hiring demand",
                        "note": "Demand index 58/100",
                        "weight": "medium",
                        "direction": "up"
                    },
                    {
                        "name": "Automation exposure",
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                        "weight": "high",
                        "direction": "steady"
                    },
                    {
                        "name": "Real wage growth",
                        "note": "13.0% after 7.0% inflation",
                        "weight": "high",
                        "direction": "up"
                    },
                    {
                        "name": "Scenario growth",
                        "note": "20.0% modelled nominal growth",
                        "weight": "high",
                        "direction": "up"
                    }
                ]
            }
        ]
    },
    "skills": [],
    "sources": [
        {
            "name": "Iran",
            "url": null,
            "type": "nearest_donor",
            "tier": "derived"
        },
        {
            "name": "Belgium",
            "url": null,
            "type": "nearest_donor",
            "tier": "derived"
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    ],
    "faqs": [
        {
            "question": "What is the average salary of a Machine Learning Engineer in Pakistan?",
            "answer": "SpotSalary models a median annual salary of ₨15.5M for a Machine Learning Engineer in Pakistan, or about ₨1,287,694 per month before tax. The middle 50% of the estimate ranges from ₨11.3M to ₨19.7M, with a full P10–P90 range of ₨8.4M to ₨22.3M. This is a modelled estimate, not a job offer."
        },
        {
            "question": "How much does an entry-level Machine Learning Engineer earn in Pakistan?",
            "answer": "The entry-level band for a Machine Learning Engineer in Pakistan centres on ₨7.5M per year (P25–P75: ₨6.3M–₨8.5M). Entry-level pay typically covers the first 2 years of experience and depends on company size, skills and responsibilities."
        },
        {
            "question": "How much does a senior or executive Machine Learning Engineer earn in Pakistan?",
            "answer": "The executive band for a Machine Learning Engineer in Pakistan has a median of ₨30.3M per year and a P75 of ₨34.9M. Senior and executive packages often include a larger bonus and equity component; this benchmark shows the total-compensation split for each level."
        },
        {
            "question": "What is the salary outlook for a Machine Learning Engineer in Pakistan?",
            "answer": "The outlook is growing. In the base scenario, median pay reaches ₨38.5M by 2031, about 148.8% above today before inflation and 13.0% per year in real terms after 7.0% inflation. Scenario bands widen over time and are not guarantees."
        },
        {
            "question": "What is the take-home pay for a Machine Learning Engineer in Pakistan?",
            "answer": "After an effective income tax rate of 29.7%, the mid-level Machine Learning Engineer in Pakistan takes home about ₨10,863,011 per year, or ₨905,251 per month. The estimate uses imported national tax brackets and does not include social contributions or local levies."
        },
        {
            "question": "How does SpotSalary calculate these salary estimates?",
            "answer": "Estimates are anchored to external market signals — GDP per capita PPP, inflation, wage growth, cost of living, demand and automation exposure — and synthesised with AI. Deterministic validation rejects implausible outputs. This report carries 58% confidence and draws on 15 salary observations."
        }
    ],
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        ],
        "occupation_hub": "https://www.spotsalary.com/occupations/machine-learning-engineer",
        "location_hub": "https://www.spotsalary.com/locations/pakistan-pk",
        "all_salaries": "https://www.spotsalary.com/salaries"
    },
    "citation": {
        "plain": "Machine Learning Engineer Salary in Pakistan. SpotSalary. https://www.spotsalary.com/salary/machine-learning-engineer/pakistan-pk",
        "updated_at": "2026-10-30T15:10:38+00:00"
    }
}